Chapter 3
Imogen Poyntz-Wright
2023-03-23
#Load libraries
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library(readr)
library(openxlsx)
library(dplyr)
library(MuMIn)
library(tidyr)
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## %nin%, center#Load datasets
midlandsdataMOA <-read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/final dataset for species_family richness MOA2 completed_temp_flow.csv")
anglaindataMOA <- read_csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work/FINAL DATASETS 36 days/final anglian dataset MOA complete_flow_temp.csv")## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
## dat <- vroom(...)
## problems(dat)## Rows: 1862 Columns: 34
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): SAMPLE_DATE.y, MY.DATE1
## dbl (30): SITE_ID.y, DAY, MONTH, YEAR, distinctfamilies, distinctspp, julian...
## lgl (2): Fumarate.reductase, gamma.aminobutyric.acid
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.GABA_ACHE_SITE1 <- read_csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/53594 ACHE and GABA.csv")## Rows: 2218 Columns: 18
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (9): sample.samplingPoint.notation, sample.samplingPoint.label, sample.s...
## dbl (9): DAY, YEAR, result, Easting, Northing, Latitude, Longitude, SITE_ID,...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.#Subset data MOA
midlandsdataMOA$dates <- as.Date(midlandsdataMOA$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdataMOA$SITE_ID<- as.character(midlandsdataMOA$SITE_ID.y) #add site id as character
anglaindataMOA$dates <- as.Date(anglaindataMOA$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindataMOA$SITE_ID<- as.character(anglaindataMOA$SITE_ID.y) #add site id as character
midlandsdata_50020 <- subset(midlandsdataMOA, SITE_ID.y %in% c('50020'))
midlandsdata_50020$dates <- as.Date(midlandsdata_50020$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_50020$SITE_ID<- as.character(midlandsdata_50020$SITE_ID.y) #add site id as character
midlandsdata_53594 <- subset(midlandsdataMOA, SITE_ID.y %in% c('53594'))
midlandsdata_53594$dates <- as.Date(midlandsdata_53594$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_53594$SITE_ID<- as.character(midlandsdata_53594$SITE_ID.y) #add site id as character
midlandsdata_53846 <- subset(midlandsdataMOA, SITE_ID %in% c('53846'))
midlandsdata_53846$dates <- as.Date(midlandsdata_53846$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_53846$SITE_ID<- as.character(midlandsdata_53846$SITE_ID.y) #add site id as character
midlandsdata_47046 <- subset(midlandsdataMOA, SITE_ID %in% c('47046'))
midlandsdata_47046$dates <- as.Date(midlandsdata_47046$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_47046$SITE_ID<- as.character(midlandsdata_47046$SITE_ID.y) #add site id as character
midlandsdata_47138 <- subset(midlandsdataMOA, SITE_ID %in% c('47138'))
midlandsdata_47138$dates <- as.Date(midlandsdata_47138$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_47138$SITE_ID<- as.character(midlandsdata_47138$SITE_ID.y) #add site id as character
midlandsdata_47157 <- subset(midlandsdataMOA, SITE_ID %in% c('47157'))
midlandsdata_47157$dates <- as.Date(midlandsdata_47157$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_47157$SITE_ID<- as.character(midlandsdata_47157$SITE_ID.y) #add site id as character
midlandsdata_47255 <- subset(midlandsdataMOA, SITE_ID %in% c('47255'))
midlandsdata_47255$dates <- as.Date(midlandsdata_47255$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_47255$SITE_ID<- as.character(midlandsdata_47255$SITE_ID.y) #add site id as character
midlandsdata_48226 <- subset(midlandsdataMOA, SITE_ID %in% c('48226'))
midlandsdata_48226$dates <- as.Date(midlandsdata_48226$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_48226$SITE_ID<- as.character(midlandsdata_48226$SITE_ID.y) #add site id as character
midlandsdata_49881 <- subset(midlandsdataMOA, SITE_ID.y %in% c('49881'))
midlandsdata_49881$dates <- as.Date(midlandsdata_49881$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_49881$SITE_ID<- as.character(midlandsdata_49881$SITE_ID.y) #add site id as character
midlandsdata_50031 <- subset(midlandsdataMOA, SITE_ID %in% c('50031'))
midlandsdata_50031$dates <- as.Date(midlandsdata_50031$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_50031$SITE_ID<- as.character(midlandsdata_50031$SITE_ID.y) #add site id as character
midlandsdata_50139 <- subset(midlandsdataMOA, SITE_ID %in% c('50139'))
midlandsdata_50139$dates <- as.Date(midlandsdata_50139$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_50139$SITE_ID<- as.character(midlandsdata_50139$SITE_ID.y) #add site id as character
midlandsdata_50257 <- subset(midlandsdataMOA, SITE_ID %in% c('50257'))
midlandsdata_50257$dates <- as.Date(midlandsdata_50257$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_50257$SITE_ID<- as.character(midlandsdata_50257$SITE_ID.y) #add site id as character
midlandsdata_50440 <- subset(midlandsdataMOA, SITE_ID %in% c('50440'))
midlandsdata_50440$dates <- as.Date(midlandsdata_50440$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_50440$SITE_ID<- as.character(midlandsdata_50440$SITE_ID.y) #add site id as character
midlandsdata_51097 <- subset(midlandsdataMOA, SITE_ID %in% c('51097'))
midlandsdata_51097$dates <- as.Date(midlandsdata_51097$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_51097$SITE_ID<- as.character(midlandsdata_51097$SITE_ID.y) #add site id as character
midlandsdata_51357 <- subset(midlandsdataMOA, SITE_ID %in% c('51357'))
midlandsdata_51357$dates <- as.Date(midlandsdata_51357$MY.DATE1, "%m/%d/%Y") #add date as date
midlandsdata_51357$SITE_ID<- as.character(midlandsdata_51357$SITE_ID.y) #add site id as character
anglaindata_55006 <- subset(anglaindataMOA, SITE_ID %in% c('55006'))
anglaindata_55006$dates <- as.Date(anglaindata_55006$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55006$SITE_ID<- as.character(anglaindata_55006$SITE_ID.y) #add site id as character
anglaindata_55088 <- subset(anglaindataMOA, SITE_ID %in% c('55088'))
anglaindata_55088$dates <- as.Date(anglaindata_55088$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55088$SITE_ID<- as.character(anglaindata_55088$SITE_ID.y) #add site id as character
anglaindata_55311 <- subset(anglaindataMOA, SITE_ID %in% c('55311'))
anglaindata_55311$dates <- as.Date(anglaindata_55311$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55311$SITE_ID<- as.character(anglaindata_55311$SITE_ID.y) #add site id as character
anglaindata_55350 <- subset(anglaindataMOA, SITE_ID %in% c('55350'))
anglaindata_55350$dates <- as.Date(anglaindata_55350$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55350$SITE_ID<- as.character(anglaindata_55350$SITE_ID.y) #add site id as character
anglaindata_55436 <- subset(anglaindataMOA, SITE_ID %in% c('55436'))
anglaindata_55436$dates <- as.Date(anglaindata_55436$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55436$SITE_ID<- as.character(anglaindata_55436$SITE_ID.y) #add site id as character
anglaindata_55566 <- subset(anglaindataMOA, SITE_ID %in% c('55566'))
anglaindata_55566$dates <- as.Date(anglaindata_55566$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55566$SITE_ID<- as.character(anglaindata_55566$SITE_ID.y) #add site id as character
anglaindata_55833a <- subset(anglaindataMOA, SITE_ID.y %in% c('55833'))
anglaindata_55833a$dates <- as.Date(anglaindata_55833a$MY.DATE1, "%m/%d/%Y") #add date as date
anglaindata_55833a$SITE_ID<- as.character(anglaindata_55833a$SITE_ID.y) #add site id as character
fam_spp <- read_csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/All families and species.csv")## Rows: 293759 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Species, Family
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.GABA_53594_acute <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/53594 ACHE acute subgroup.csv")
GABA_53594_acute2 <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/53594 GABA ACUTE FIELD.csv")
GABA_53594_chronic <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/53594 ACHE chronic subgroup.csv")
GABA_53594_chronic2 <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work midlands/Midlands final datasets 36 days/53594 GABA chronic.csv")#Site 1 - 53594 Testing ACHE and GABA on family richness
##AChE pesticides
##Process data for PCA analysis
pca_data<- subset(midlandsdata_53594, select = c( 5, 10,13, 29, 16,17, 21, 20, 25, 27, 40))
midpca_data_53594_sodium<- subset(pca_data, select = c( 4:11))
pca_data1 <- midpca_data_53594_sodium %>% drop_na()
pca_dataa <- pca_data %>% drop_na()
##Run PCA analysis
###Normalised data
midpca_data_53594_all.data_normalized <- scale(pca_data1)
midpca_data_53594_all.pca1 <- prcomp(midpca_data_53594_all.data_normalized, center=TRUE, scale.=TRUE)
fviz_pca_var(midpca_data_53594_all.pca1,axes = c(1, 3))
pcs <- as.data.frame(midpca_data_53594_all.pca1$x)
###model data
angres.pca <- PCA(midpca_data_53594_all.data_normalized, graph = FALSE)
print(angres.pca)## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 44 individuals, described by 8 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"###retrieve data
var <- get_pca_var(angres.pca)
###Correlation plot
fviz_pca_var(angres.pca, col.var = "black")
corrplot(var$cos2, is.corr=FALSE)
#ggsave(P1, file="Contribution table of variables across all PCAs.png")
### Total cos2 of variables on Dim.1 and Dim.2
angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
### Color by cos2 values: quality on the factor map
angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid text overlapping
###Contributions of variables to PCs
corrplot(var$contrib, is.corr=FALSE)
### Contributions of variables to PC1
angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
angpca1a <- angpca1 +theme(axis.text=element_text(size=12),
axis.title=element_text(size=14,face="bold"))
ggtitle("Contibution of varibales to PC1 AChE") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))## NULL ### Contributions of variables to PC2
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
angpca2a <- angpca2 +theme(axis.text=element_text(size=12, angle = 90,),
axis.title=element_text(size=14,face="bold"))
ggtitle("Contibution of varibales to PC2 AChE") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))## NULL ### Contributions of variables to PC3
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 3, top = 10)
angpca2a <- angpca2 +theme(axis.text=element_text(size=12, angle = 90,),
axis.title=element_text(size=14,face="bold"))
ggtitle("Contibution of varibales to PC3 AChE") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))## NULL ###The total contribution to PC1 and PC2
fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
###highlighting most important values
angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
#RUN GLM Analaysis - poisson distribution (count data)
###Process data
PCA_53593_ACHE <- cbind(pca_dataa, pcs) #add PC to dataset
PCA_53593_ACHE1 <- transform(PCA_53593_ACHE, day_in_year_cs = scale(day_in_year), pc1_cs = scale(PC1), pc2_cs= scale(PC2)) ###transfrom
###Run entire model
PCA_53593_ACHE1_MODEL <- glm(distinct_families ~ PC1 + PC2 + PC3 + day_in_year + YEAR, family = ("poisson"), data=PCA_53593_ACHE1)
summary(PCA_53593_ACHE1_MODEL) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year +
## YEAR, family = ("poisson"), data = PCA_53593_ACHE1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.81066 -0.57766 -0.01416 0.41249 2.04430
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 24.5794669 26.1155913 0.941 0.3466
## PC1 -0.0956637 0.0513636 -1.862 0.0625 .
## PC2 -0.0623299 0.0489245 -1.274 0.2027
## PC3 -0.0649571 0.0368318 -1.764 0.0778 .
## day_in_year -0.0001684 0.0007781 -0.216 0.8287
## YEAR -0.0107056 0.0130322 -0.821 0.4114
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 50.515 on 43 degrees of freedom
## Residual deviance: 31.978 on 38 degrees of freedom
## AIC: 261.75
##
## Number of Fisher Scoring iterations: 4###Model selection
options(na.action = "na.fail")
dredge1 <- dredge(PCA_53593_ACHE1_MODEL, rank = "AIC")## Fixed term is "(Intercept)"#write.table(dredge1, file = "AICc 53593 ACHE.txt", sep = ",")
###Run selected model - after AICc selection (accounting for all 3 PCs = 80% variance)
PCA_53593_ACHE1_MODEL_2 <- glm(distinct_families ~ PC1 + PC2 + PC3 + YEAR, family = ("poisson"), data=PCA_53593_ACHE1)
summary(PCA_53593_ACHE1_MODEL_2) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + YEAR, family = ("poisson"),
## data = PCA_53593_ACHE1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.84671 -0.58001 -0.03471 0.39564 2.03173
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 23.30096 25.40584 0.917 0.3591
## PC1 -0.08985 0.04372 -2.055 0.0399 *
## PC2 -0.06863 0.03931 -1.746 0.0808 .
## PC3 -0.06722 0.03535 -1.902 0.0572 .
## YEAR -0.01008 0.01270 -0.794 0.4270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 50.515 on 43 degrees of freedom
## Residual deviance: 32.025 on 39 degrees of freedom
## AIC: 259.8
##
## Number of Fisher Scoring iterations: 4PCA_53593_ACHE1_MODEL_2 <- glm(distinct_families ~ PC1 + day_in_year, family = ("poisson"), data=PCA_53593_ACHE1)
summary(PCA_53593_ACHE1_MODEL_2) ##
## Call:
## glm(formula = distinct_families ~ PC1 + day_in_year, family = ("poisson"),
## data = PCA_53593_ACHE1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.27992 -0.49276 -0.04958 0.48795 2.34417
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.2838246 0.0868997 37.789 < 2e-16 ***
## PC1 -0.0754745 0.0197477 -3.822 0.000132 ***
## day_in_year -0.0007775 0.0003982 -1.952 0.050887 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 50.515 on 43 degrees of freedom
## Residual deviance: 35.642 on 41 degrees of freedom
## AIC: 259.42
##
## Number of Fisher Scoring iterations: 4summ(PCA_53593_ACHE1_MODEL_2, confint = TRUE, digits = 3)## MODEL INFO:
## Observations: 44
## Dependent Variable: distinct_families
## Type: Generalized linear model
## Family: poisson
## Link function: log
##
## MODEL FIT:
## χ²(2) = 14.873, p = 0.001
## Pseudo-R² (Cragg-Uhler) = 0.287
## Pseudo-R² (McFadden) = 0.055
## AIC = 259.416, BIC = 264.768
##
## Standard errors: MLE
## -------------------------------------------------------------
## Est. 2.5% 97.5% z val. p
## ----------------- -------- -------- -------- -------- -------
## (Intercept) 3.284 3.114 3.454 37.789 0.000
## PC1 -0.075 -0.114 -0.037 -3.822 0.000
## day_in_year -0.001 -0.002 0.000 -1.952 0.051
## -------------------------------------------------------------###test model for overdispersion
testDispersion(PCA_53593_ACHE1_MODEL_2)
##
## DHARMa nonparametric dispersion test via sd of residuals fitted vs.
## simulated
##
## data: simulationOutput
## dispersion = 0.84296, p-value = 0.464
## alternative hypothesis: two.sidedsimPCA_53593_ACHE1_MODEL_2_Fam<- simulateResiduals(PCA_53593_ACHE1_MODEL_2, refit=T)
testOverdispersion(simPCA_53593_ACHE1_MODEL_2_Fam)## testOverdispersion is deprecated, switch your code to using the testDispersion function
##
## DHARMa nonparametric dispersion test via mean deviance residual fitted
## vs. simulated-refitted
##
## data: simulationOutput
## dispersion = 0.88051, p-value = 0.56
## alternative hypothesis: two.sidedplot(simPCA_53593_ACHE1_MODEL_2_Fam)
##GABA pesticides
##Process data for PCA analysis
pca_data<- subset(midlandsdata_53594, select = c( 5, 10,13, 33, 16,17, 20, 25,27, 40))
midpca_data_53594_sodium<- subset(pca_data, select = c( 4:10))
pca_data1 <- midpca_data_53594_sodium %>% drop_na()
pca_dataa <- pca_data %>% drop_na()
##Run PCA analysis
###Normalised data
midpca_data_53594_all.data_normalized <- scale(pca_data1)
midpca_data_53594_all.pca1 <- prcomp(midpca_data_53594_all.data_normalized, center=TRUE, scale.=TRUE)
fviz_pca_var(midpca_data_53594_all.pca1,axes = c(1, 3))
pcs <- as.data.frame(midpca_data_53594_all.pca1$x)
###model data
angres.pca <- PCA(midpca_data_53594_all.data_normalized, graph = FALSE)
print(angres.pca)## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 61 individuals, described by 7 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"###retrieve data
var <- get_pca_var(angres.pca)
###Correlation plot
fviz_pca_var(angres.pca, col.var = "black")
corrplot(var$cos2, is.corr=FALSE)
### Total cos2 of variables on Dim.1 and Dim.2
angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
### Color by cos2 values: quality on the factor map
angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid text overlapping)
###Contributions of variables to PCs
corrplot(var$contrib, is.corr=FALSE) 
### Contributions of variables to PC1
angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
angpca1a <- angpca1 +theme(axis.text=element_text(size=12),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("Ammoniacal Nitrogen", "Ammonia", "pH", "BOD","Orthophosphate", "Temperature", "GABA pesticide")) +
ggtitle("Contibution of varibales to PC1") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))
### Contributions of variables to PC2
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
angpca2a <- angpca2 +theme(axis.text=element_text(size=12, angle = 90,),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("Orthophosphate", "BOD", "pH","Temperature", "GABA pesticide", "Ammonia", "Ammoniacal Nitrogen")) +
ggtitle("Contibution of varibales to PC2") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))
### Contributions of variables to PC3
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 3, top = 10)
angpca2a <- angpca2 +theme(axis.text=element_text(size=12, angle = 90,),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("GABA pesticide", "Temperature", "Ammonia","BOD", "pH", "Orthophosphate", "Ammoniacal Nitrogen")) +
ggtitle("Contibution of varibales to PC3") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5,))
###The total contribution to PC1 and PC2
fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
###highlighting most important values
angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
#RUN GLM Analaysis - poisson distribution (count data)
###Process data
PCA_53593_GABA <- cbind(pca_dataa, pcs) #add PC to dataset
PCA_53593_GABA_1 <- transform(PCA_53593_GABA, day_in_year_cs = scale(day_in_year), pc1_cs = scale(PC1), pc2_cs= scale(PC2)) ###transfrom
###Run entire model
PCA_53593_GABA_1_MODEL <- glm(distinct_families ~ PC1 + PC2 + PC3 + day_in_year + YEAR, family = ("poisson"), data=PCA_53593_GABA_1)
summary(PCA_53593_GABA_1_MODEL) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year +
## YEAR, family = ("poisson"), data = PCA_53593_GABA_1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.00631 -0.54638 0.00495 0.43317 1.69553
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.436e+01 1.496e+01 -0.960 0.337033
## PC1 -1.976e-02 3.835e-02 -0.515 0.606373
## PC2 5.890e-02 4.009e-02 1.469 0.141769
## PC3 -1.472e-01 4.470e-02 -3.294 0.000987 ***
## day_in_year 1.484e-03 7.024e-04 2.113 0.034564 *
## YEAR 8.563e-03 7.489e-03 1.143 0.252881
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 82.979 on 60 degrees of freedom
## Residual deviance: 37.187 on 55 degrees of freedom
## AIC: 346.18
##
## Number of Fisher Scoring iterations: 4###Model selection
options(na.action = "na.fail")
dredge1 <- dredge(PCA_53593_GABA_1_MODEL, rank = "AIC")## Fixed term is "(Intercept)"#write.table(dredge1, file = "AICc 53593 GABA.txt", sep = ",")
###Run selected model - after AICc selection (accounting for all 3 PCs = 80% variance)
PCA_53593_GABA1_MODEL_2 <- glm(distinct_families ~ PC1 + PC2 + PC3 + day_in_year, family = ("poisson"), data=PCA_53593_GABA_1)
summary(PCA_53593_GABA1_MODEL_2) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year,
## family = ("poisson"), data = PCA_53593_GABA_1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.75922 -0.57063 0.04196 0.44365 1.69268
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.7417052 0.1429148 19.184 < 2e-16 ***
## PC1 -0.0533489 0.0249078 -2.142 0.032205 *
## PC2 0.0872633 0.0314670 2.773 0.005551 **
## PC3 -0.1564510 0.0440091 -3.555 0.000378 ***
## day_in_year 0.0014993 0.0007015 2.137 0.032579 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 82.979 on 60 degrees of freedom
## Residual deviance: 38.501 on 56 degrees of freedom
## AIC: 345.49
##
## Number of Fisher Scoring iterations: 4PCA_53593_GABA1_MODEL_2 <- glm(distinct_families ~ PC3 + day_in_year +YEAR , family = ("poisson"), data=PCA_53593_GABA_1)
summary(PCA_53593_GABA1_MODEL_2) ##
## Call:
## glm(formula = distinct_families ~ PC3 + day_in_year + YEAR, family = ("poisson"),
## data = PCA_53593_GABA_1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.06289 -0.57484 -0.02019 0.50049 1.83393
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.044e+01 6.437e+00 -4.730 2.25e-06 ***
## PC3 -1.129e-01 3.327e-02 -3.392 0.000693 ***
## day_in_year 9.502e-04 3.758e-04 2.529 0.011447 *
## YEAR 1.666e-02 3.221e-03 5.173 2.30e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 82.979 on 60 degrees of freedom
## Residual deviance: 39.404 on 57 degrees of freedom
## AIC: 344.4
##
## Number of Fisher Scoring iterations: 4summ(PCA_53593_GABA1_MODEL_2, confint = TRUE, digits = 3)## MODEL INFO:
## Observations: 61
## Dependent Variable: distinct_families
## Type: Generalized linear model
## Family: poisson
## Link function: log
##
## MODEL FIT:
## χ²(3) = 43.575, p = 0.000
## Pseudo-R² (Cragg-Uhler) = 0.511
## Pseudo-R² (McFadden) = 0.115
## AIC = 344.395, BIC = 352.839
##
## Standard errors: MLE
## ----------------------------------------------------------------
## Est. 2.5% 97.5% z val. p
## ----------------- --------- --------- --------- -------- -------
## (Intercept) -30.442 -43.057 -17.827 -4.730 0.000
## PC3 -0.113 -0.178 -0.048 -3.392 0.001
## day_in_year 0.001 0.000 0.002 2.529 0.011
## YEAR 0.017 0.010 0.023 5.173 0.000
## ----------------------------------------------------------------###test model for overdispersion
testDispersion(PCA_53593_GABA1_MODEL_2)
##
## DHARMa nonparametric dispersion test via sd of residuals fitted vs.
## simulated
##
## data: simulationOutput
## dispersion = 0.70737, p-value = 0.112
## alternative hypothesis: two.sidedsimPCA_53593_GABA1_MODEL_2_FAM<- simulateResiduals(PCA_53593_GABA1_MODEL_2, refit=T)
testOverdispersion(simPCA_53593_GABA1_MODEL_2_FAM)## testOverdispersion is deprecated, switch your code to using the testDispersion function
##
## DHARMa nonparametric dispersion test via mean deviance residual fitted
## vs. simulated-refitted
##
## data: simulationOutput
## dispersion = 0.68835, p-value = 0.048
## alternative hypothesis: two.sidedplot(simPCA_53593_GABA1_MODEL_2_FAM)
#Site 2 - 50020 ##AChE
##process data
pca_data<- subset(midlandsdata_50020, select = c( 29, 16:17, 19:21, 27))
midpca_data_50020_all <- pca_data %>% drop_na()
##run PCA analysis
#Normalised data
midpca_data_50020_all.data_normalized <- scale(midpca_data_50020_all)
midpca_data_50020_all.pca1 <- prcomp(midpca_data_50020_all.data_normalized, center=TRUE, scale.=TRUE)
fviz_pca_var(midpca_data_50020_all.pca1,axes = c(1, 3))
pcs <- as.data.frame(midpca_data_50020_all.pca1$x)
#model data
angres.pca <- PCA(midpca_data_50020_all.data_normalized, graph = FALSE)
print(angres.pca)## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 32 individuals, described by 7 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"#retrieve data
var <- get_pca_var(angres.pca)
###Correlation plot
fviz_pca_var(angres.pca, col.var = "black")
corrplot(var$cos2, is.corr=FALSE)
### Total cos2 of variables on Dim.1 and Dim.2
angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
### Color by cos2 values: quality on the factor map
angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid text overlapping)
###Contributions of variables to PCs
corrplot(var$contrib, is.corr=FALSE) 
### Contributions of variables to PC1
angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
### Contributions of variables to PC2
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 3, top = 10)
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 4, top = 10)
###The total contribution to PC1 and PC2
fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
###highlighting most important values
angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
##PCA model for test
pca_data<- subset(midlandsdata_50020, select = c(5, 10,13, 29, 16:17, 19:21, 27, 28, 39, 40,41,42))
pca_data1 <- pca_data %>% drop_na()
pca_data_3<- subset(pca_data1, select = c(1,2,3, 11, 14, 15))
PCA_50020_all <- cbind(pca_data_3, pcs)
p1<- ggplot(pca_data1, aes(x = AChE, y = distinct_families)) +geom_point() +geom_smooth(method = "lm", se= FALSE)
###Scale other variables
datmidland_50020_ACHE_CS <- transform(PCA_50020_all, dates_cs=scale(dates), day_in_year_cs = scale(day_in_year))
###run modeL ENTIRE
datmidland_50020_ACHE_all_fam <- glm(distinct_families ~ PC1 + PC2 + PC3 + day_in_year_cs + YEAR, family =("poisson"), data=datmidland_50020_ACHE_CS)
summary(datmidland_50020_ACHE_all_fam) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year_cs +
## YEAR, family = ("poisson"), data = datmidland_50020_ACHE_CS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.47039 -0.35205 0.05484 0.48469 1.28138
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -17.007952 23.035918 -0.738 0.460
## PC1 -0.031881 0.028567 -1.116 0.264
## PC2 0.009540 0.040165 0.238 0.812
## PC3 0.005525 0.039403 0.140 0.888
## day_in_year_cs 0.043827 0.049990 0.877 0.381
## YEAR 0.010200 0.011533 0.884 0.376
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 19.504 on 31 degrees of freedom
## Residual deviance: 14.076 on 26 degrees of freedom
## AIC: 192.49
##
## Number of Fisher Scoring iterations: 4###Model selection
options(na.action = "na.fail")
dredge1 <- dredge(datmidland_50020_ACHE_all_fam, rank = "AIC")## Fixed term is "(Intercept)"#write.table(dredge1, file = "AICc 53593 GABA.txt", sep = ",")
datmidland_50020_ACHE_all_fam <- glm(distinct_families ~ YEAR, family =("poisson"), data=datmidland_50020_ACHE_CS)
summary(datmidland_50020_ACHE_all_fam) ##
## Call:
## glm(formula = distinct_families ~ YEAR, family = ("poisson"),
## data = datmidland_50020_ACHE_CS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.47783 -0.54053 -0.08047 0.62349 1.20708
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -26.567682 16.551542 -1.605 0.1085
## YEAR 0.014987 0.008286 1.809 0.0705 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 19.504 on 31 degrees of freedom
## Residual deviance: 16.226 on 30 degrees of freedom
## AIC: 186.64
##
## Number of Fisher Scoring iterations: 4#Null model better than PCA (80%)##GABA
##process data
pca_data<- subset(midlandsdata_50020, select = c( 33, 16:17, 19:21, 27))
midpca_data_50020_all <- pca_data %>% drop_na()
##run PCA analysis
#Normalised data
midpca_data_50020_all.data_normalized <- scale(midpca_data_50020_all)
midpca_data_50020_all.pca1 <- prcomp(midpca_data_50020_all.data_normalized, center=TRUE, scale.=TRUE)
fviz_pca_var(midpca_data_50020_all.pca1,axes = c(1, 3))
pcs <- as.data.frame(midpca_data_50020_all.pca1$x)
#model data
angres.pca <- PCA(midpca_data_50020_all.data_normalized, graph = FALSE)
print(angres.pca)## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 31 individuals, described by 7 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"#retrieve data
var <- get_pca_var(angres.pca)
###Correlation plot
fviz_pca_var(angres.pca, col.var = "black")
corrplot(var$cos2, is.corr=FALSE)
### Total cos2 of variables on Dim.1 and Dim.2
angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
### Color by cos2 values: quality on the factor map
angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid text overlapping)
###Contributions of variables to PCs
corrplot(var$contrib, is.corr=FALSE) 
### Contributions of variables to PC1
angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
### Contributions of variables to PC2
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 3, top = 10)
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 4, top = 10)
###The total contribution to PC1 and PC2
fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
###highlighting most important values
angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
##PCA model for test
pca_data<- subset(midlandsdata_50020, select = c(5, 10,13, 33, 16:17, 19:21, 27, 28, 39, 40,41,42))
pca_data1 <- pca_data %>% drop_na()
pca_data_3<- subset(pca_data1, select = c(1,2,3, 11, 14, 15))
PCA_50020_all <- cbind(pca_data_3, pcs)
###Scale other variables
datmidland_50020_GABA_CS <- transform(PCA_50020_all, dates_cs=scale(dates), day_in_year_cs = scale(day_in_year))
###run modeL ENTIRE
datmidland_50020_GABA_all_fam <- glm(distinct_families ~ PC1 + PC2 + PC3 + day_in_year_cs + YEAR, family =("poisson"), data=datmidland_50020_GABA_CS)
summary(datmidland_50020_GABA_all_fam) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year_cs +
## YEAR, family = ("poisson"), data = datmidland_50020_GABA_CS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.36843 -0.43112 0.01903 0.45178 1.42915
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -16.779409 19.343837 -0.867 0.386
## PC1 0.025871 0.027827 0.930 0.353
## PC2 0.014030 0.035941 0.390 0.696
## PC3 -0.020253 0.037903 -0.534 0.593
## day_in_year_cs 0.034971 0.051348 0.681 0.496
## YEAR 0.010082 0.009684 1.041 0.298
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 18.660 on 30 degrees of freedom
## Residual deviance: 12.959 on 25 degrees of freedom
## AIC: 186
##
## Number of Fisher Scoring iterations: 4###Model selection
options(na.action = "na.fail")
dredge1 <- dredge(datmidland_50020_GABA_all_fam, rank = "AIC")## Fixed term is "(Intercept)"#write.table(dredge1, file = "AICc 53593 GABA.txt", sep = ",")
datmidland_50020_GABA_all_fam <- glm(distinct_families ~ YEAR, family =("poisson"), data=datmidland_50020_GABA_CS)
summary(datmidland_50020_GABA_all_fam) ##
## Call:
## glm(formula = distinct_families ~ YEAR, family = ("poisson"),
## data = datmidland_50020_GABA_CS)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.46583 -0.51081 -0.07504 0.53518 1.24092
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -27.846411 16.649391 -1.673 0.0944 .
## YEAR 0.015623 0.008335 1.875 0.0609 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 18.660 on 30 degrees of freedom
## Residual deviance: 15.135 on 29 degrees of freedom
## AIC: 180.18
##
## Number of Fisher Scoring iterations: 4#Null model better than PCA (80%)#Site 3 - 53846 ##GABA
###processing data
pca_data<- subset(midlandsdata_53846, select = c(5, 10, 13, 17, 20, 21, 27,33, 40, 28, 41,42))
midlandsdata_53846_GABA <- pca_data %>% drop_na()
midlandsdata_53846_GABA1<- subset(midlandsdata_53846_GABA, select = c( 4:9))
midlandsdata_53846_GABA1A<- subset(midlandsdata_53846_GABA, select = c( 3:9))
###running PCA
###Normalised data
midlandsdata_53846_GABA.data_normalized <- scale(midlandsdata_53846_GABA1)
midlandsdata_53846_GABA.pca1 <- prcomp(midlandsdata_53846_GABA.data_normalized, center=TRUE, scale.=TRUE)
fviz_pca_var(midlandsdata_53846_GABA.pca1,axes = c(1, 3))
pcs <- as.data.frame(midlandsdata_53846_GABA.pca1$x)
###model data
angres.pca <- PCA(midlandsdata_53846_GABA.data_normalized, graph = FALSE)
print(angres.pca)## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 35 individuals, described by 6 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"###retrieve data
var <- get_pca_var(angres.pca)
###Correlation plot
fviz_pca_var(angres.pca, col.var = "black")
corrplot(var$cos2, is.corr=FALSE)
### Total cos2 of variables on Dim.1 and Dim.2
angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
### Color by cos2 values: quality on the factor map
angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid text overlapping)
### Contributions of variables to PCs
corrplot(var$contrib, is.corr=FALSE) 
### Contributions of variables to PC1
angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
angpca1a <- angpca1 +theme(axis.text=element_text(size=12),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("Temperature", "Ammonical Nitrogen", "Dissolved Oxygen", "GABA Pesticide","Ammonia", "pH")) +
ggtitle("Contibution of varibales to PC1")
### Contributions of variables to PC2
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
angpca2a<- angpca2 +theme(axis.text=element_text(size=12),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("Ammonia", "pH", "Dissolved Oxygen", "GABA Pesticide","Temperature", "Ammonical Nitrogen")) +
ggtitle("Contibution of varibales to PC2")
### Contributions of variables to PC3
angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 3, top = 10)
angpca2a<- angpca2 +theme(axis.text=element_text(size=12),
axis.title=element_text(size=14,face="bold")) +
scale_x_discrete(labels=c("pH", "Ammonial Nitrogen", "GABA Pesticide", "Dissolved Oxygen", "Temperature", "Ammonia")) +
ggtitle("Contibution of varibales to PC3")
### The total contribution to PC1 and PC2
fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
### highlighting most important values
angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))
### PCA model for test
PCA_53593_GABA <- cbind(midlandsdata_53846_GABA, pcs)
midlandsdata_53846_GABA_1 <- transform(PCA_53593_GABA, dates_cs=scale(dates), day_in_year_cs = scale(day_in_year), pc1_cs = scale(PC1), pc2_cs= scale(PC2))
#run modeL ENITRE MODEL
midlandsdata_53846_GABA_fam <- glm(distinct_families ~ PC1 + PC2 +PC3 + day_in_year_cs +YEAR, family=("poisson"),data=midlandsdata_53846_GABA_1)
summary(midlandsdata_53846_GABA_fam) ##
## Call:
## glm(formula = distinct_families ~ PC1 + PC2 + PC3 + day_in_year_cs +
## YEAR, family = ("poisson"), data = midlandsdata_53846_GABA_1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.53747 -0.38381 0.06505 0.30619 1.20429
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -40.554620 17.863614 -2.270 0.0232 *
## PC1 0.045000 0.063246 0.712 0.4768
## PC2 -0.036353 0.053235 -0.683 0.4947
## PC3 -0.034701 0.057832 -0.600 0.5485
## day_in_year_cs 0.031944 0.092549 0.345 0.7300
## YEAR 0.021660 0.008919 2.429 0.0152 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 27.139 on 34 degrees of freedom
## Residual deviance: 11.625 on 29 degrees of freedom
## AIC: 186.6
##
## Number of Fisher Scoring iterations: 4 ###Model selection
options(na.action = "na.fail")
dredge1 <- dredge(midlandsdata_53846_GABA_fam, rank = "AIC")## Fixed term is "(Intercept)"#write.table(dredge1, file = "AICc 53593 GABA.txt", sep = ",")
###run modeL
midlandsdata_53846_GABA_fam <- glm(distinct_families ~ YEAR, family=("poisson"),data=midlandsdata_53846_GABA_1)
summary(midlandsdata_53846_GABA_fam) ##
## Call:
## glm(formula = distinct_families ~ YEAR, family = ("poisson"),
## data = midlandsdata_53846_GABA_1)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.71953 -0.29833 0.05998 0.34088 1.27514
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -27.823486 8.306378 -3.350 0.000809 ***
## YEAR 0.015303 0.004145 3.692 0.000223 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for poisson family taken to be 1)
##
## Null deviance: 27.139 on 34 degrees of freedom
## Residual deviance: 13.498 on 33 degrees of freedom
## AIC: 180.48
##
## Number of Fisher Scoring iterations: 4#NO PC important#Site 4 - 55006 ##NA NOT ANY OTHER CHEMICAL INFO ##GABA
#Processing
#subset data and reomve NAs
# pca_data<- subset(anglaindata_55006, select = c( 6,7,10, 13, 16, 17, 21, 22, 24, 25,29, 35, 36))
#angliandata_55006A <- pca_data %>% drop_na()
#pca_data1<- subset(angliandata_55006A, select = c( 4:11))
#Normalised data
#midlandsdata_47046_GABA.data_normalized <- scale(pca_data1)
#midlandsdata_47046_GABA.pca1 <- prcomp(midlandsdata_47046_GABA.data_normalized, center=TRUE, scale.=TRUE)
#fviz_pca_var(midlandsdata_47046_GABA.pca1,axes = c(1, 2))
#pcs <- as.data.frame(midlandsdata_47046_GABA.pca1$x)
#model data
#angres.pca <- PCA(midlandsdata_47046_GABA.data_normalized, graph = FALSE)
#print(angres.pca)
#retrieve data
#var <- get_pca_var(angres.pca)
#Correlation plot
#fviz_pca_var(angres.pca, col.var = "black")
#corrplot(var$cos2, is.corr=FALSE)
# Total cos2 of variables on Dim.1 and Dim.2
#angplot1pca<- fviz_cos2(angres.pca, choice = "var", axes = 1:2)
# Color by cos2 values: quality on the factor map
#angplot2pca<- fviz_pca_var(angres.pca, col.var = "cos2",
# gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
# repel = TRUE # Avoid text overlapping
#)
#Contributions of variables to PCs
#corrplot(var$contrib, is.corr=FALSE)
# Contributions of variables to PC1
# angpca1 <- fviz_contrib(angres.pca, choice = "var", axes = 1, top = 10)
# Contributions of variables to PC2
#angpca2 <- fviz_contrib(angres.pca, choice = "var", axes = 2, top = 10)
#The total contribution to PC1 and PC2
#fviz_contrib(angres.pca, choice = "var", axes = 1:2, top = 10)
#highlighting most important values
#angplot3pca<- fviz_pca_var(angres.pca, col.var = "contrib",
# gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"))#All Family and Species
###remove duplicates
fam_spp1<- fam_spp[!duplicated(fam_spp$Species ),]
###Extract
write.xlsx(fam_spp1, file = "All family and species no duplicates.xlsx")#Plots for Lab vs field
#FOR AChE 53594 CHRONIC
#FOR GABA_53594
p1 <- ggplot(GABA_53594_chronic, aes(x = chemical_mean, y = Source, colour = Endpoint)) +
geom_point( position = position_jitterdodge(), alpha=1, size = 1.3) +
scale_x_continuous(trans='log10') +theme_bw() + facet_wrap(~Family, ncol=4) +
scale_y_discrete(limits = c("Field", "Azinphos-methly", "Azinphos-ethyl","Chlorfenvinphos", "Coumaphos", "Carbophenothion", "Demeton-S-methyl" ,"Diazinon","Dichlorvos","Dimethoate", "Fenitrothion", "Fenthion", "Malathion","Mevinphos", "Omethoate" ,"Parathion-ethyl", "Parathion-methyl", "Propetamphos", "Triazophos")) +xlab("Chemical concentration (\u00B5g/l)") + ylab("Chemcial source") + theme(text = element_text(size = 20)) +
geom_vline(xintercept = 0.72, color = "red", linewidth=0.5) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5)) +
geom_segment(aes(x =0.0, y = "Triazophos", xend = 0.01, yend = "Triazophos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Propetamphos", xend = 0.3 , yend = "Propetamphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-methyl", xend = 0.015, yend = "Parathion-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-ethyl", xend = 0.01, yend = "Parathion-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Omethoate", xend = 0.01, yend = "Omethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Mevinphos", xend = 0.025 , yend = "Mevinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Malathion", xend = 0.02, yend = "Malathion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenthion", xend = 0.02 , yend = "Fenthion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenitrothion", xend = 0.02, yend = "Fenitrothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dimethoate", xend = 0.01, yend = "Dimethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Diazinon", xend = 0.16, yend = "Diazinon"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dichlorvos", xend = 0.05, yend = "Dichlorvos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Demeton-S-methyl", xend = 0.01, yend = "Demeton-S-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Carbophenothion", xend = 0.01, yend = "Carbophenothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Coumaphos", xend = 0.01, yend = "Coumaphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Chlorfenvinphos", xend = 0.11 , yend = "Chlorfenvinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-ethyl", xend = 0.05, yend = "Azinphos-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-methly", xend = 0.05, yend = "Azinphos-methly"), color = "black", linewidth = 0.5)
p1## Warning: Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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ggsave(p1, file = "53594 Family ACHE subgroup v2 receptor chronic boxplot.png", height = 6, width = 12)## Warning: Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis #FOR AChE 53594 Acute
#FOR GABA_53594
p1 <- ggplot(GABA_53594_acute, aes(x = chemical_mean, y = Source, colour = Endpoint)) +
geom_point(position = position_jitterdodge(), alpha=1, size = 1.3) +
scale_x_continuous(trans='log10') +theme_bw() +
facet_wrap(~Family, ncol =4) +
scale_y_discrete(limits = c("Field", "Azinphos-methly", "Azinphos-ethyl","Chlorfenvinphos", "Coumaphos", "Carbophenothion", "Demeton-S-methyl" ,"Diazinon","Dichlorvos","Dimethoate", "Fenitrothion", "Fenthion", "Malathion","Mevinphos", "Omethoate" ,"Parathion-ethyl", "Parathion-methyl", "Propetamphos", "Triazophos")) +xlab("Chemical concentration (\u00B5g/l)") +
ylab("Chemcial source")+ theme(text = element_text(size = 20)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5)) +
geom_vline(xintercept = 0.72, color = "red", linewidth=0.5) +
geom_segment(aes(x =0.0, y = "Triazophos", xend = 0.01, yend = "Triazophos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Propetamphos", xend = 0.3 , yend = "Propetamphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-methyl", xend = 0.015, yend = "Parathion-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-ethyl", xend = 0.01, yend = "Parathion-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Omethoate", xend = 0.01, yend = "Omethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Mevinphos", xend = 0.025 , yend = "Mevinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Malathion", xend = 0.02, yend = "Malathion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenthion", xend = 0.02 , yend = "Fenthion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenitrothion", xend = 0.02, yend = "Fenitrothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dimethoate", xend = 0.01, yend = "Dimethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Diazinon", xend = 0.16, yend = "Diazinon"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dichlorvos", xend = 0.05, yend = "Dichlorvos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Demeton-S-methyl", xend = 0.01, yend = "Demeton-S-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Carbophenothion", xend = 0.01, yend = "Carbophenothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Coumaphos", xend = 0.01, yend = "Coumaphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Chlorfenvinphos", xend = 0.11 , yend = "Chlorfenvinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-ethyl", xend = 0.05, yend = "Azinphos-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-methly", xend = 0.05, yend = "Azinphos-methly"), color = "black", linewidth = 0.5)
p1 ## Warning: Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis## Warning: Removed 8 rows containing missing values (`geom_point()`).
#ggsave(p1, file = "53594 Family ACHE subgroup v2 receptor acute boxplot.png", height = 10, width = 12)
#FOR GABA 53594 Acute
#FOR GABA_53594 CHRONIC
p1 <- ggplot(GABA_53594_acute2, aes(x = GABA_receptor, y = Source, colour = Endpoint)) +
geom_point(position = position_jitterdodge(), alpha=1, size = 1.3) +
scale_x_continuous(trans='log10') +theme_bw() +
facet_wrap(~Family, ncol =4) +
scale_y_discrete(limits = c("Field", "Aldrin", "Dieldrin","Endrin", "Heptachlor", "Lindane")) + xlab("Chemical concentration (\u00B5g/l)") +
ylab("Chemcial source")+ theme(text = element_text(size = 20)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5)) +
geom_vline(xintercept = 0.0476, color = "red", linewidth=0.5) +
#ggsave(p1, file = "53594 Family GABA receptor acute boxplot.png", height = 20, width = 12)+
geom_segment(aes(x =0.0, y = "Triazophos", xend = 0.01, yend = "Triazophos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Propetamphos", xend = 0.3 , yend = "Propetamphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-methyl", xend = 0.015, yend = "Parathion-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Parathion-ethyl", xend = 0.01, yend = "Parathion-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Omethoate", xend = 0.01, yend = "Omethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Mevinphos", xend = 0.025 , yend = "Mevinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Malathion", xend = 0.02, yend = "Malathion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenthion", xend = 0.02 , yend = "Fenthion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Fenitrothion", xend = 0.02, yend = "Fenitrothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dimethoate", xend = 0.01, yend = "Dimethoate"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Diazinon", xend = 0.16, yend = "Diazinon"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Dichlorvos", xend = 0.05, yend = "Dichlorvos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Demeton-S-methyl", xend = 0.01, yend = "Demeton-S-methyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Carbophenothion", xend = 0.01, yend = "Carbophenothion"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Coumaphos", xend = 0.01, yend = "Coumaphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Chlorfenvinphos", xend = 0.11 , yend = "Chlorfenvinphos"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-ethyl", xend = 0.05, yend = "Azinphos-ethyl"), color = "black", linewidth = 0.5) +
geom_segment(aes(x =0.0, y = "Azinphos-methly", xend = 0.05, yend = "Azinphos-methly"), color = "black", linewidth = 0.5)
p1 ## Warning: Transformation introduced infinite values in continuous x-axis## Warning: Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
## Transformation introduced infinite values in continuous x-axis
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## Transformation introduced infinite values in continuous x-axis## Warning: Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
## Removed 1522 rows containing missing values (`geom_segment()`).
# ggsave(p1, file = "53594 Family ACHE subgroup v2 receptor acute boxplot.png", height = 10, width = 12)#Identifying highest concentrations of chemicals per site
##Load dataset
Angliandata <-read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work/Final datasets for analysis/Final datasets for mergance/all chemical data 16_01_23_overlap_sites.csv")
Midlanddata <-read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/ALL Midlands data for merging/Midlands chem final overlap data.csv")
#Anglia
data_new2<- Angliandata %>%
group_by(determinand.definition, SITE_ID, MOA, Longitude, Latitude) %>%
summarise(max = max(result, na.rm=TRUE))## `summarise()` has grouped output by 'determinand.definition', 'SITE_ID', 'MOA',
## 'Longitude'. You can override using the `.groups` argument.#write.table(data_new2, file='Maximum concentrations for chemicals at sites in Anglia.txt', sep=',')
#Midlands
data_new3<- Midlanddata %>%
group_by(determinand.definition, SITE_ID, MOA, Longitude, Latitude) %>%
summarise(max = max(result, na.rm=TRUE))## `summarise()` has grouped output by 'determinand.definition', 'SITE_ID', 'MOA',
## 'Longitude'. You can override using the `.groups` argument.#write.table(data_new3, file='Maximum concentrations for chemicals at sites in Midlands.txt', sep=',')#Identifying highest concentrations of chemicals per site over time (per year)
##Load dataset
Angliandata <-read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work/Final datasets for analysis/Final datasets for mergance/all chemical data 16_01_23_overlap_sites.csv")
Midlanddata <-read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/ALL Midlands data for merging/Midlands chem final overlap data.csv")
total_data <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Andrew data analysis extra/all chemical data 12_07_23.csv")
data_subset_AChE <- total_data[total_data$MOA %in% c('AChE inhibition'),]
data_subset_GABA <- total_data[total_data$MOA %in% c('GABA receptor'),]
#All data - mean conc per year
#GABA
data_subset_GABA_conc <- data_subset_GABA %>%
group_by(YEAR) %>%
summarise(mean = mean(result, na.rm=TRUE))
#AChE
data_subset_AChE_conc <- data_subset_AChE %>%
group_by(YEAR) %>%
summarise(mean = mean(result, na.rm=TRUE))
#All data - max conc per year
#GABA
data_subset_GABA_conc_max <- data_subset_GABA %>%
group_by(YEAR) %>%
summarise(max = max(result, na.rm=TRUE))
#AChE
data_subset_AChE_conc_max <- data_subset_AChE %>%
group_by(YEAR) %>%
summarise(max = max(result, na.rm=TRUE))
##PLOTS
#GABA
GABA_mean <- ggplot(data_subset_GABA_conc, aes(x = YEAR, y = mean)) +
geom_bar(stat="identity", fill="steelblue")+
theme_minimal() +ylab("Mean concentration (µg/l)") +xlab("Year") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5))
GABA_max <- ggplot(data_subset_GABA_conc_max, aes(x = YEAR, y = max)) +
geom_bar(stat="identity", fill="steelblue")+
theme_minimal() +ylab("Max concentration (µg/l)") +xlab("Year") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5))
#ACHE
ACHE_mean <- ggplot(data_subset_AChE_conc, aes(x = YEAR, y = mean)) +
geom_bar(stat="identity", fill="steelblue")+
theme_minimal() +ylab("Mean concentration (µg/l)") +xlab("Year") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5))
ACHE_max <- ggplot(data_subset_AChE_conc_max, aes(x = YEAR, y = max)) +
geom_bar(stat="identity", fill="steelblue")+
theme_minimal() +ylab("Max concentration (µg/l)") +xlab("Year") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5))
#ARABLE PERCENTAGE VS PESTICIDE CONC
#All data - mean conc per year
#ALL
total_data_arable_conc <- total_data %>%
group_by(SITE_ID, arable_perc) %>%
summarise(mean = mean(result, na.rm=TRUE))## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. total_data_arable_conc_max <- total_data %>%
group_by(SITE_ID, arable_perc) %>%
summarise(max = max(result, na.rm=TRUE))## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. #GABA
data_GABA_arable_conc <- data_subset_GABA %>%
group_by(SITE_ID, arable_perc) %>%
summarise(mean = mean(result, na.rm=TRUE))## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. #AChE
data_ACHE_arable_conc <- data_subset_AChE %>%
group_by(SITE_ID, arable_perc) %>%
summarise(mean = mean(result, na.rm=TRUE)) ## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. #All data - max conc per year
#GABA
data_GABA_arable_conc_max <- data_subset_GABA %>%
group_by(SITE_ID, arable_perc) %>%
summarise(max = max(result, na.rm=TRUE))## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. #AChE
data_ACHE_arable_conc_max <- data_subset_AChE %>%
group_by(SITE_ID, arable_perc) %>%
summarise(max = max(result, na.rm=TRUE)) ## `summarise()` has grouped output by 'SITE_ID'. You can override using the
## `.groups` argument. #plot
geom_smooth(method = "lm", se = FALSE)## geom_smooth: na.rm = FALSE, orientation = NA, se = FALSE
## stat_smooth: na.rm = FALSE, orientation = NA, se = FALSE, method = lm
## position_identity #GABA
GABA_arable_mean <- ggplot(data_GABA_arable_conc, aes(x = arable_perc, y = mean)) +
geom_point() +
theme_minimal() +ylab("Mean concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5, size = 20),
axis.title.x = element_text(vjust = -1.5, size = 20))
ggsave(GABA_arable_mean, file=("GABA_arable_mean.tiff"), dpi = 330)## Saving 7 x 5 in image GABA_arable_max <- ggplot(data_GABA_arable_conc_max, aes(x = arable_perc, y = max)) +
geom_point() +
theme_minimal() +ylab("Max concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5, size = 20),
axis.title.x = element_text(vjust = -1.5, size = 20))
ggsave(GABA_arable_max, file=("GABA_arable_max.tiff"), dpi = 330)## Saving 7 x 5 in image #AChE
AChE_arable_mean <- ggplot(data_ACHE_arable_conc, aes(x = arable_perc, y = mean)) +
geom_point() +
theme_minimal() +ylab("Mean concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5, size = 20),
axis.title.x = element_text(vjust = -1.5, size = 20))
ggsave(AChE_arable_mean, file=("AChE_arable_mean.tiff"), dpi = 330)## Saving 7 x 5 in image AChE_arable_max <- ggplot(data_ACHE_arable_conc_max, aes(x = arable_perc, y = max)) +
geom_point() +
theme_minimal() +ylab("Max concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5, size = 20),
axis.title.x = element_text(vjust = -1.5, size = 20))
ggsave(AChE_arable_max, file=("AChE_arable_max.tiff"), dpi = 330)## Saving 7 x 5 in image #All
All_arable_mean <- ggplot(total_data_arable_conc, aes(x = arable_perc, y = mean)) +
geom_point() +
theme_minimal() +ylab("Mean concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5)) +
scale_y_continuous(trans='log2')
All_arable_max <- ggplot(total_data_arable_conc_max, aes(x = arable_perc, y = max)) +
geom_point() + geom_smooth() +
theme_minimal() +ylab("Max concentration (µg/l)") +xlab("Percentage of arable farming upstream") +
theme(text=element_text(size=16), axis.title.y = element_text(vjust = +1.5),
axis.title.x = element_text(vjust = -1.5))#Relationship between sites with threshold exceedances of chemical conc vs macroinvert data
#Load datasets
fam_rich <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/ALL Midlands data for merging/family richness data.csv")
fam_rich2 <- read.csv("C:/Users/imoge/OneDrive/phd/Research/Objective 4/Paper work/Final datasets for analysis/Final datasets for mergance/family richness final data.csv")
fam_rich$MY.DATE1 <- do.call(paste, list(fam_rich$MONTH, fam_rich$DAY, fam_rich$YEAR))
fam_rich$MY.DATE1 <- as.Date(fam_rich$MY.DATE1, format=c("%m %d %Y"))
fam_rich2$MY.DATE1 <- do.call(paste, list(fam_rich2$MONTH, fam_rich2$DAY, fam_rich2$YEAR))
fam_rich2$MY.DATE1 <- as.Date(fam_rich2$MY.DATE1, format=c("%m %d %Y"))
#calculate single all pesticides value for each sample date
total_data_day <- total_data %>%
group_by(DAY, MONTH, YEAR, SITE_ID) %>%
summarise(mean = mean(result, na.rm=TRUE))## `summarise()` has grouped output by 'DAY', 'MONTH', 'YEAR'. You can override
## using the `.groups` argument. total_data_day$MY.DATE1 <- do.call(paste, list(total_data_day$MONTH, total_data_day$DAY, total_data_day$YEAR))
total_data_day$MY.DATE1 <- as.Date(total_data_day$MY.DATE1, format=c("%m %d %Y"))
#merge datasets - ALL pesticide
data_all_fam_conc0 <- rbind(total_data_day,fam_rich)
data_all_fam_conc <- rbind(data_all_fam_conc0,fam_rich2)
#calculate single MOA pesticides value for each sample date
total_data_day_ACHE <- data_subset_AChE %>%
group_by(DAY, MONTH, YEAR, SITE_ID) %>%
summarise(mean = mean(result, na.rm=TRUE))## `summarise()` has grouped output by 'DAY', 'MONTH', 'YEAR'. You can override
## using the `.groups` argument. total_data_day_ACHE$MY.DATE1 <- do.call(paste, list(total_data_day_ACHE$MONTH, total_data_day_ACHE$DAY, total_data_day_ACHE$YEAR))
total_data_day_ACHE$MY.DATE1 <- as.Date(total_data_day_ACHE$MY.DATE1, format=c("%m %d %Y"))
#Merge datasets for only AChE
data_all_fam_conc_ACHE0 <- rbind(total_data_day_ACHE,fam_rich)
data_all_fam_conc_ACHE <- rbind(data_all_fam_conc_ACHE0,fam_rich2)
#calculate single MOA pesticides value for each sample date
total_data_day_GABA <- data_subset_GABA %>%
group_by(DAY, MONTH, YEAR, SITE_ID) %>%
summarise(mean = mean(result, na.rm=TRUE))## `summarise()` has grouped output by 'DAY', 'MONTH', 'YEAR'. You can override
## using the `.groups` argument. total_data_day_GABA$MY.DATE1 <- do.call(paste, list(total_data_day_GABA$MONTH, total_data_day_GABA$DAY, total_data_day_GABA$YEAR))
total_data_day_GABA$MY.DATE1 <- as.Date(total_data_day_GABA$MY.DATE1, format=c("%m %d %Y"))
data_all_fam_conc_GABA0 <- rbind(total_data_day_GABA,fam_rich)
data_all_fam_conc_GABA <- rbind(data_all_fam_conc_GABA0,fam_rich2)
coeff = 100
PLOT_total <- ggplot(data_all_fam_conc_GABA, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue")+ scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#Select sites and run plots - comapring macro richness and conc pesticides over time
#47138
#ONLY EXCEEDENCE IS Parathion-methyl which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_47138 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('47138'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_47138 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('47138'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_47138 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('47138'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_47138 <- ggplot(data_all_fam_conc_47138, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_47138_ACHE <- ggplot(data_all_fam_conc_ACHE_47138, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("47138 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_47138_GABA <- ggplot(data_all_fam_conc_GABA_47138, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("47138 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#47255
#EXCEEDENCE of Parathion-methyl, Malathion, Azinphos-methyl, Fenitrothion, Fipronil, Mevinphos
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_47255 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('47255'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_47255 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('47255'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_47255 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('47255'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_47255 <- ggplot(data_all_fam_conc_47255, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff2), size=2, color = "blue") + scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_47255_ACHE <- ggplot(data_all_fam_conc_ACHE_47255, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff2), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("47255 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_47255_GABA <- ggplot(data_all_fam_conc_GABA_47255, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("47255 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#48583
#EXCEEDENCE of Parathion-methyl, Fenitrothion, Diazinon
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_48583 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('48583'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_48583 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('48583'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_48583 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('48583'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_48583 <- ggplot(data_all_fam_conc_48583, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff2), size=2, color = "blue") + scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_48583_ACHE <- ggplot(data_all_fam_conc_ACHE_48583, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff2), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") + scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("48583 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_48583_GABA <- ggplot(data_all_fam_conc_GABA_48583, aes(x=MY.DATE1)) + geom_point( aes(y=distinct_families),
size=2, color= "red") + geom_point (aes(y=mean*coeff), size=2, color = "blue") + geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("48583 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#49881
#EXCEEDENCE of Parathion-methyl, Malathion, Diazinon, Carbaryl (ALL ACHE INHIBITORS)
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_49881 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('49881'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_49881 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('49881'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_49881 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('49881'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide -YES
PLOT_49881 <- ggplot(data_all_fam_conc_49881, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide -YES
PLOT_49881_ACHE <- ggplot(data_all_fam_conc_ACHE_49881, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("49881 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_49881_GABA <- ggplot(data_all_fam_conc_GABA_49881, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("49881 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#50020
#EXCEEDENCE of Parathion-methyl,
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_50020 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('50020'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_50020 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('50020'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_50020 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('50020'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide -YES
PLOT_50020 <- ggplot(data_all_fam_conc_50020, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide -YES
PLOT_50020_ACHE <- ggplot(data_all_fam_conc_ACHE_50020, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50020 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_50020_GABA <- ggplot(data_all_fam_conc_GABA_50020, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50020 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#50031
#EXCEEDENCE of Parathion-methyl, Malathion, Fenitrothion, Dichlorvos, Phorate
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_50031<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('50031'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_50031 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('50031'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_50031 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('50031'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide -
PLOT_550031 <- ggplot(data_all_fam_conc_50031, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_50031_ACHE <- ggplot(data_all_fam_conc_ACHE_50031, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
#geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50031 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_50031_GABA <- ggplot(data_all_fam_conc_GABA_50031, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50031 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#50139
#EXCEEDENCE of Parathion-methyl, Malathion, Dichlorvos, Carbaryl, Diazinon
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_50139<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('50139'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_50139 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('50139'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_50139 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('50139'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_50139 <- ggplot(data_all_fam_conc_50139, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_50139_ACHE <- ggplot(data_all_fam_conc_ACHE_50139, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff2), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50139 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_50139_GABA <- ggplot(data_all_fam_conc_GABA_50139, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic()+
ggtitle("50139 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#50257
#EXCEEDENCE of Parathion-methyl Azinphos-methyl, Malathion, Dichlorvos
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_50257<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('50257'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_50257 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('50257'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_50257 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('50257'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_50257 <- ggplot(data_all_fam_conc_50257, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_50257_ACHE <- ggplot(data_all_fam_conc_ACHE_50257, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff2), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50257 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_50257_GABA <- ggplot(data_all_fam_conc_GABA_50257, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("50257 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#51097
#EXCEEDENCE of Parathion-methyl
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_51097<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('51097'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_51097 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('51097'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_51097 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('51097'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_51097 <- ggplot(data_all_fam_conc_51097, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_51097_ACHE <- ggplot(data_all_fam_conc_ACHE_51097, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff2), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51097 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_51097_GABA <- ggplot(data_all_fam_conc_GABA_51097, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51097 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#51357
#EXCEEDENCE of Parathion-methyl
#which the threshold conc based on lab data is very low 0.00031 µg/l
data_all_fam_conc_51357<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('51357'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_51357 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('51357'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_51357 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('51357'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_51357 <- ggplot(data_all_fam_conc_51357, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_51357_ACHE <- ggplot(data_all_fam_conc_ACHE_51357, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
#geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51357 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_51357_GABA <- ggplot(data_all_fam_conc_GABA_51357, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51357 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#51392
#EXCEEDENCE of Phorate
data_all_fam_conc_51392<- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('51392'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_51392 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('51392'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_51392 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('51392'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_51392 <- ggplot(data_all_fam_conc_51392, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
#geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_51392_ACHE <- ggplot(data_all_fam_conc_ACHE_51392, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51392 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_51392_GABA <- ggplot(data_all_fam_conc_GABA_51392, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51392 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#51634
#EXCEEDENCE of Dichlorvos
data_all_fam_conc_51634 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('51634'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_51634 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('51634'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_51634 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('51634'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_51634 <- ggplot(data_all_fam_conc_51634, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
#geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_51634_ACHE <- ggplot(data_all_fam_conc_ACHE_51634, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51634 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_51634_GABA <- ggplot(data_all_fam_conc_GABA_51634, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("51634 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#53594
#EXCEEDENCE of Parathion-methyl, Dichlorvos, Fipronil, Diazinon
coeff=100
data_all_fam_conc_53594 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('53594'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_53594 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('53594'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_53594 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('53594'),]
#SELECT SITE ALL PESTCIDE
coeff2 = 10
#ALL pesticide
PLOT_53594 <- ggplot(data_all_fam_conc_53594, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_53594_ACHE <- ggplot(data_all_fam_conc_ACHE_53594, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 1 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
ggsave(PLOT_53594_ACHE, file=("PLOT 53594 ACHE.png"), width = 14, height = 20, units = "cm", dpi=300)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 332 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 73 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 332 rows containing missing values (`geom_point()`).## Warning: Removed 73 rows containing missing values (`geom_point()`).coeff = 100
#GABA pesticide
PLOT_53594_GABA <- ggplot(data_all_fam_conc_GABA_53594, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 1 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#53846
#EXCEEDENCE of Diazinon Parathion-methyl
data_all_fam_conc_53846 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('53846'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_53846 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('53846'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_53846 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('53846'),]
#SELECT SITE ALL PESTCIDE
coeff2 = 10
#ALL pesticide
PLOT_53846 <- ggplot(data_all_fam_conc_53846, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_53846_ACHE <- ggplot(data_all_fam_conc_ACHE_53846, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13)) +
ggtitle("Site 53846 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
coeff= 1000
#GABA pesticide
PLOT_53846_GABA <- ggplot(data_all_fam_conc_GABA_53846, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13)) +
ggtitle("Site 53846 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#55006
#EXCEEDENCE of
data_all_fam_conc_55006 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('55006'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_55006 <- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('55006'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_55006 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('55006'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_55006 <- ggplot(data_all_fam_conc_55006, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13)) +
ggtitle("Site 53846 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#ACHE pesticide
PLOT_55006_ACHE <- ggplot(data_all_fam_conc_ACHE_55006, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13)) +
ggtitle("Site 55006 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_55006_GABA <- ggplot(data_all_fam_conc_GABA_55006, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13)) +
ggtitle("Site 55006 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#55088
#EXCEEDENCE of
data_all_fam_conc_55088 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('55088'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_55088<- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('55088'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_55088 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('55088'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_55088 <- ggplot(data_all_fam_conc_55088, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_55088_ACHE <- ggplot(data_all_fam_conc_ACHE_55088, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55088 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_55088_GABA <- ggplot(data_all_fam_conc_GABA_55088, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55088 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#55436
#EXCEEDENCE of
data_all_fam_conc_55436 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('55436'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_55436<- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('55436'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_55436 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('55436'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_55436 <- ggplot(data_all_fam_conc_55436, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_55436_ACHE <- ggplot(data_all_fam_conc_ACHE_55436, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55436 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_55436_GABA <- ggplot(data_all_fam_conc_GABA_55436, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55436 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#55833
#EXCEEDENCE of
data_all_fam_conc_55833 <- data_all_fam_conc[data_all_fam_conc$SITE_ID %in% c('55833'),] #SELECT SITE ALL PESTCIDE
data_all_fam_conc_ACHE_55833<- data_all_fam_conc_ACHE[data_all_fam_conc_ACHE$SITE_ID %in% c('55833'),]
#SELECT SITE ALL PESTCIDE
data_all_fam_conc_GABA_55833 <- data_all_fam_conc_GABA[data_all_fam_conc_GABA$SITE_ID %in% c('55833'),]
#SELECT SITE ALL PESTCIDE
#ALL pesticide
PLOT_55833 <- ggplot(data_all_fam_conc_55833, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
theme(axis.title.y = element_text(size=13),axis.title.y.right = element_text(size=13))
#ACHE pesticide
PLOT_55833_ACHE <- ggplot(data_all_fam_conc_ACHE_55833, aes(x=MY.DATE1)) +
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55833 ACHE") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
#GABA pesticide
PLOT_55833_GABA <- ggplot(data_all_fam_conc_GABA_55833, aes(x=MY.DATE1))+
geom_point( aes(y=distinct_families),
size=0.5, color= "red") + geom_point (aes(y=mean*coeff), size=0.5, color = "blue") +
geom_smooth(aes(y=distinct_families), method="loess", col="red") +
geom_smooth(aes(y=mean*coeff),method="loess", col="blue") +
scale_y_continuous(
# Features of the first axis
name = "Family richness",
# Add a second axis and specify its features
sec.axis = sec_axis(trans=~., name="Mean concentration*Coeff (µg/l)")) + theme_classic() +
ggtitle("Site 55833 GABA") +
xlab("Time") +
theme(plot.title = element_text(size = 20,
face = "bold", hjust=0.5), axis.title.y = element_text(size=20, face= "bold"), axis.title.y.right = element_text(size=20, face= "bold", vjust=1), axis.title.x = element_text(size = 20, face = "bold")) + theme(text=element_text(size=20))
ggsave(PLOT_53594_ACHE, file=("PLOT 53594 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 332 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 73 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 332 rows containing missing values (`geom_point()`).## Warning: Removed 73 rows containing missing values (`geom_point()`).ggsave(PLOT_53594_GABA, file=("PLOT 53594 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 514 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 73 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 514 rows containing missing values (`geom_point()`).## Warning: Removed 73 rows containing missing values (`geom_point()`).ggsave(PLOT_53846_ACHE, file=("PLOT 53846 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 32 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 69 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 32 rows containing missing values (`geom_point()`).## Warning: Removed 69 rows containing missing values (`geom_point()`).ggsave(PLOT_53846_GABA, file=("PLOT 53846 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 315 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 69 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 315 rows containing missing values (`geom_point()`).## Warning: Removed 69 rows containing missing values (`geom_point()`).ggsave(PLOT_55006_ACHE, file=("PLOT 55006 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 125 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 71 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 125 rows containing missing values (`geom_point()`).## Warning: Removed 71 rows containing missing values (`geom_point()`).ggsave(PLOT_55006_GABA, file=("PLOT 55006 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 261 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 71 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 261 rows containing missing values (`geom_point()`).## Warning: Removed 71 rows containing missing values (`geom_point()`).ggsave(PLOT_55088_ACHE, file=("PLOT 55088 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 78 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 85 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 78 rows containing missing values (`geom_point()`).## Warning: Removed 85 rows containing missing values (`geom_point()`).ggsave(PLOT_55088_GABA, file=("PLOT 55088 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 45 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 85 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 45 rows containing missing values (`geom_point()`).## Warning: Removed 85 rows containing missing values (`geom_point()`).ggsave(PLOT_55436_ACHE, file=("PLOT 55436 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 79 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 56 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 79 rows containing missing values (`geom_point()`).## Warning: Removed 56 rows containing missing values (`geom_point()`).ggsave(PLOT_55436_GABA, file=("PLOT 55436 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 452 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 56 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 452 rows containing missing values (`geom_point()`).## Warning: Removed 56 rows containing missing values (`geom_point()`).ggsave(PLOT_55833_ACHE, file=("PLOT 55833 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 78 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 53 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 78 rows containing missing values (`geom_point()`).## Warning: Removed 53 rows containing missing values (`geom_point()`).ggsave(PLOT_55833_GABA, file=("PLOT 55833 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 326 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 53 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 326 rows containing missing values (`geom_point()`).## Warning: Removed 53 rows containing missing values (`geom_point()`).ggsave(PLOT_51634_ACHE, file=("PLOT 51634 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 24 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 55 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 24 rows containing missing values (`geom_point()`).## Warning: Removed 55 rows containing missing values (`geom_point()`).ggsave(PLOT_51634_GABA, file=("PLOT 51634 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 17 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 55 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 17 rows containing missing values (`geom_point()`).## Warning: Removed 55 rows containing missing values (`geom_point()`).ggsave(PLOT_51392_ACHE, file=("PLOT 51392 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 129 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 76 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 129 rows containing missing values (`geom_point()`).## Warning: Removed 76 rows containing missing values (`geom_point()`).ggsave(PLOT_51392_GABA, file=("PLOT 51392 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 76 rows containing non-finite values (`stat_smooth()`).
## Removed 76 rows containing missing values (`geom_point()`).ggsave(PLOT_51357_ACHE, file=("PLOT 51357 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 181 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 181 rows containing missing values (`geom_point()`).## Warning: Removed 59 rows containing missing values (`geom_point()`).ggsave(PLOT_51357_GABA, file=("PLOT 51357 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 18 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 59 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 18 rows containing missing values (`geom_point()`).## Warning: Removed 59 rows containing missing values (`geom_point()`).ggsave(PLOT_51097_ACHE, file=("PLOT 51097 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 21 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 76 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 21 rows containing missing values (`geom_point()`).## Warning: Removed 76 rows containing missing values (`geom_point()`).ggsave(PLOT_51097_GABA, file=("PLOT 51097 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 11 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 76 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 11 rows containing missing values (`geom_point()`).## Warning: Removed 76 rows containing missing values (`geom_point()`).ggsave(PLOT_50257_ACHE, file=("PLOT 50257 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 27 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 51 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 27 rows containing missing values (`geom_point()`).## Warning: Removed 51 rows containing missing values (`geom_point()`).ggsave(PLOT_50257_GABA, file=("PLOT 50257 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 40 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 51 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 40 rows containing missing values (`geom_point()`).## Warning: Removed 51 rows containing missing values (`geom_point()`).ggsave(PLOT_50139_ACHE, file=("PLOT 50139 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 92 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 60 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 92 rows containing missing values (`geom_point()`).## Warning: Removed 60 rows containing missing values (`geom_point()`).ggsave(PLOT_50139_GABA, file=("PLOT 50139 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 88 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 60 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 88 rows containing missing values (`geom_point()`).## Warning: Removed 60 rows containing missing values (`geom_point()`).ggsave(PLOT_50031_ACHE, file=("PLOT 50031 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 133 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 133 rows containing missing values (`geom_point()`).## Warning: Removed 82 rows containing missing values (`geom_point()`).ggsave(PLOT_50031_GABA, file=("PLOT 50031 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 82 rows containing non-finite values (`stat_smooth()`).
## Removed 82 rows containing missing values (`geom_point()`).ggsave(PLOT_50020_ACHE, file=("PLOT 50020 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 147 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 89 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 147 rows containing missing values (`geom_point()`).## Warning: Removed 89 rows containing missing values (`geom_point()`).ggsave(PLOT_50020_GABA, file=("PLOT 50020 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 150 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 89 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 150 rows containing missing values (`geom_point()`).## Warning: Removed 89 rows containing missing values (`geom_point()`).ggsave(PLOT_49881_ACHE, file=("PLOT 49881 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 194 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 53 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 194 rows containing missing values (`geom_point()`).## Warning: Removed 53 rows containing missing values (`geom_point()`).ggsave(PLOT_49881_GABA, file=("PLOT 49881 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 5 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 53 rows containing non-finite values (`stat_smooth()`).## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : span too small. fewer data values than degrees of freedom.## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : pseudoinverse used at 7352.4## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : neighborhood radius 561.6## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : reciprocal condition number 0## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : There are other near singularities as well. 1.3797e+06## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : span too small. fewer
## data values than degrees of freedom.## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used at
## 7352.4## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 561.6## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal condition
## number 0## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other near
## singularities as well. 1.3797e+06## Warning: Removed 5 rows containing missing values (`geom_point()`).## Warning: Removed 53 rows containing missing values (`geom_point()`).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning
## -Infggsave(PLOT_48583_ACHE, file=("PLOT 48583 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 5 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 51 rows containing non-finite values (`stat_smooth()`).## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : span too small. fewer data values than degrees of freedom.## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : pseudoinverse used at 7810.5## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : neighborhood radius 51.53## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : reciprocal condition number 0## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : There are other near singularities as well. 3083.6## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : span too small. fewer
## data values than degrees of freedom.## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used at
## 7810.5## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 51.53## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal condition
## number 0## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other near
## singularities as well. 3083.6## Warning: Removed 5 rows containing missing values (`geom_point()`).## Warning: Removed 51 rows containing missing values (`geom_point()`).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning
## -Infggsave(PLOT_48583_GABA, file=("PLOT 48583 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 51 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 51 rows containing missing values (`geom_point()`).ggsave(PLOT_47255_ACHE, file=("PLOT 47255 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 112 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 60 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 112 rows containing missing values (`geom_point()`).## Warning: Removed 60 rows containing missing values (`geom_point()`).ggsave(PLOT_47255_GABA, file=("PLOT 47255 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 98 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 60 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 98 rows containing missing values (`geom_point()`).## Warning: Removed 60 rows containing missing values (`geom_point()`).ggsave(PLOT_47138_ACHE, file=("PLOT 47138 ACHE.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 5 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 83 rows containing non-finite values (`stat_smooth()`).## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : span too small. fewer data values than degrees of freedom.## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : pseudoinverse used at 9638## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : neighborhood radius 19.975## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : reciprocal condition number 0## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : There are other near singularities as well. 3.2148e+06## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : span too small. fewer
## data values than degrees of freedom.## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : pseudoinverse used at
## 9638## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : neighborhood radius
## 19.975## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : reciprocal condition
## number 0## Warning in predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x
## else if (is.data.frame(newdata))
## as.matrix(model.frame(delete.response(terms(object)), : There are other near
## singularities as well. 3.2148e+06## Warning: Removed 5 rows containing missing values (`geom_point()`).## Warning: Removed 83 rows containing missing values (`geom_point()`).## Warning in max(ids, na.rm = TRUE): no non-missing arguments to max; returning
## -Infggsave(PLOT_47138_GABA, file=("PLOT 47138 GABA.png"), height = 8, width =10)## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 144 rows containing non-finite values (`stat_smooth()`).## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 83 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 144 rows containing missing values (`geom_point()`).## Warning: Removed 83 rows containing missing values (`geom_point()`).#Samples per month by chemical at site 1
GABA_ACHE_SITE1## # A tibble: 2,218 × 18
## sample.samplingPoint.not…¹ sample.samplingPoint…² sample.sampleDateTime DAY
## <chr> <chr> <chr> <dbl>
## 1 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 2 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 3 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 4 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 5 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 6 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 7 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 8 <NA> RIVER IDLE (MAUN) - A… 05/01/1993 5
## 9 MD-38473020 RIVER IDLE (MAUN) - A… 09/01/2003 10:50 9
## 10 MD-38473020 RIVER IDLE (MAUN) - A… 24/01/2003 10:40 24
## # ℹ 2,208 more rows
## # ℹ abbreviated names: ¹sample.samplingPoint.notation,
## # ²sample.samplingPoint.label
## # ℹ 14 more variables: MONTH <chr>, YEAR <dbl>, determinand_definition <chr>,
## # class <chr>, MOA <chr>, resultQualifier.notation <chr>, result <dbl>,
## # determinand.unit.label <chr>, Easting <dbl>, Northing <dbl>,
## # Latitude <dbl>, Longitude <dbl>, SITE_ID <dbl>, Total_pest_conc <dbl>categories <- unique(GABA_ACHE_SITE1$determinand_definition)
# Loop through each value in determinand.definition
result <- GABA_ACHE_SITE1 %>%
group_by(determinand_definition, MONTH) %>%
summarize(occurrences = n())## `summarise()` has grouped output by 'determinand_definition'. You can override
## using the `.groups` argument.# Get unique determinand.definitions
unique_determinands <- unique(result$determinand_definition)
# Create a list to store plots
plot_list <- list()
#Oder by month
month_order <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")
# Loop through each determinand.definition
for (determinand in unique_determinands) {
# Filter data based on the current determinand.definition
# Filter data based on the current determinand.definition
filtered_data <- subset(result, determinand_definition == determinand)
filtered_data$MONTH <- factor(filtered_data$MONTH, levels = month_order, ordered = TRUE)
filtered_data <- na.omit(filtered_data)
# Create a bar plot using ggplot2
p <- ggplot(filtered_data, aes(x = MONTH, y = occurrences, fill = MONTH)) +
geom_bar(stat = "identity") +
labs(title = paste("", determinand),
x = "Month",
y = "Occurrences") +
theme(legend.position = "none") +
theme(plot.title = element_text(size = 32, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 18, face = "bold"),
axis.title.y = element_text(size = 18, face = "bold"), axis.text.x = element_text(size = 14), axis.text.y = element_text(size = 14))
# Store the plot in the list
plot_list[[determinand]] <- p
}
# Print each plot from the list
for (determinand in unique_determinands) {
print(plot_list[[determinand]])
filename <- paste("figures/", determinand, ".png", sep = "")
ggsave(filename, dpi = 330)
}## Saving 7 x 5 in image
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#Family richness vs pesticide concentrations over time
anglaindataMOA## # A tibble: 1,862 × 36
## SITE_ID.y SAMPLE_DATE.y DAY MONTH YEAR distinctfamilies distinctspp
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 55311 01/04/1997 1 4 1997 14 14
## 2 55311 02/03/2005 2 3 2005 17 20
## 3 55311 02/05/2006 2 5 2006 25 37
## 4 55311 03/11/1999 3 11 1999 28 38
## 5 55311 04/11/1997 4 11 1997 23 30
## 6 55311 05/05/2011 5 5 2011 19 26
## 7 55311 05/10/2016 5 10 2016 22 31
## 8 55311 06/05/2003 6 5 2003 22 32
## 9 55311 06/11/1990 6 11 1990 11 15
## 10 55311 07/10/1996 7 10 1996 8 9
## # ℹ 1,852 more rows
## # ℹ 29 more variables: MY.DATE1 <chr>, julian <dbl>, day_in_year <dbl>,
## # julian36minus <dbl>, chemical_mean <dbl>, BOD_mean <dbl>,
## # ammonia_mean <dbl>, ALTITUDE <dbl>, alkalinity_mean <dbl>,
## # ammonical_nitrogen_mean <dbl>, dissolved_oxygen_mean <dbl>,
## # hardness_mean <dbl>, nitrate_mean <dbl>, nitrite_mean <dbl>,
## # orthophosphate_mean <dbl>, oxygen_saturation_mean <dbl>, pH_mean <dbl>, …midlandsdataMOA## SITE_ID.y SAMPLE_DATE.y DAY MONTH YEAR Latitude Longitude Easting
## 1 47046 01/09/1992 1 9 1992 53.10155 -0.7994084 480481
## 2 47046 03/04/2012 3 4 2012 53.10155 -0.7994084 480481
## 3 47046 03/11/2016 3 11 2016 53.10155 -0.7994084 480481
## 4 47046 04/03/1991 4 3 1991 53.10155 -0.7994084 480481
## 5 47046 04/03/2013 4 3 2013 53.10155 -0.7994084 480481
## 6 47046 04/04/2006 4 4 2006 53.10155 -0.7994084 480481
## 7 47046 04/09/1991 4 9 1991 53.10155 -0.7994084 480481
## 8 47046 05/02/1998 5 2 1998 53.10155 -0.7994084 480481
## 9 47046 05/09/1994 5 9 1994 53.10155 -0.7994084 480481
## 10 47046 06/09/1995 6 9 1995 53.10155 -0.7994084 480481
## 11 47046 06/10/1986 6 10 1986 53.10155 -0.7994084 480481
## 12 47046 07/04/2011 7 4 2011 53.10155 -0.7994084 480481
## 13 47046 07/10/2013 7 10 2013 53.10155 -0.7994084 480481
## 14 47046 07/11/1989 7 11 1989 53.10155 -0.7994084 480481
## 15 47046 08/09/1987 8 9 1987 53.10155 -0.7994084 480481
## 16 47046 08/09/1993 8 9 1993 53.10155 -0.7994084 480481
## 17 47046 09/03/1994 9 3 1994 53.10155 -0.7994084 480481
## 18 47046 09/04/2015 9 4 2015 53.10155 -0.7994084 480481
## 19 47046 09/05/2002 9 5 2002 53.10155 -0.7994084 480481
## 20 47046 09/10/1996 9 10 1996 53.10155 -0.7994084 480481
## 21 47046 09/10/1998 9 10 1998 53.10155 -0.7994084 480481
## 22 47046 09/10/2002 9 10 2002 53.10155 -0.7994084 480481
## 23 47046 10/10/2005 10 10 2005 53.10155 -0.7994084 480481
## 24 47046 11/04/1996 11 4 1996 53.10155 -0.7994084 480481
## 25 47046 11/05/2001 11 5 2001 53.10155 -0.7994084 480481
## 26 47046 11/05/2005 11 5 2005 53.10155 -0.7994084 480481
## 27 47046 11/05/2010 11 5 2010 53.10155 -0.7994084 480481
## 28 47046 11/06/1991 11 6 1991 53.10155 -0.7994084 480481
## 29 47046 11/10/2011 11 10 2011 53.10155 -0.7994084 480481
## 30 47046 13/09/2012 13 9 2012 53.10155 -0.7994084 480481
## 31 47046 14/03/1990 14 3 1990 53.10155 -0.7994084 480481
## 32 47046 15/07/1988 15 7 1988 53.10155 -0.7994084 480481
## 33 47046 16/10/1997 16 10 1997 53.10155 -0.7994084 480481
## 34 47046 17/09/1990 17 9 1990 53.10155 -0.7994084 480481
## 35 47046 17/11/2017 17 11 2017 53.10155 -0.7994084 480481
## 36 47046 19/03/2009 19 3 2009 53.10155 -0.7994084 480481
## 37 47046 19/09/1985 19 9 1985 53.10155 -0.7994084 480481
## 38 47046 19/09/2008 19 9 2008 53.10155 -0.7994084 480481
## 39 47046 20/03/2000 20 3 2000 53.10155 -0.7994084 480481
## 40 47046 20/06/1985 20 6 1985 53.10155 -0.7994084 480481
## 41 47046 21/02/1989 21 2 1989 53.10155 -0.7994084 480481
## 42 47046 21/05/1999 21 5 1999 53.10155 -0.7994084 480481
## 43 47046 21/10/2010 21 10 2010 53.10155 -0.7994084 480481
## 44 47046 21/11/2018 21 11 2018 53.10155 -0.7994084 480481
## 45 47046 22/03/2011 22 3 2011 53.10155 -0.7994084 480481
## 46 47046 22/04/2008 22 4 2008 53.10155 -0.7994084 480481
## 47 47046 22/05/2003 22 5 2003 53.10155 -0.7994084 480481
## 48 47046 22/08/1989 22 8 1989 53.10155 -0.7994084 480481
## 49 47046 23/03/1995 23 3 1995 53.10155 -0.7994084 480481
## 50 47046 23/03/2016 23 3 2016 53.10155 -0.7994084 480481
## 51 47046 23/04/1987 23 4 1987 53.10155 -0.7994084 480481
## 52 47046 23/05/2018 23 5 2018 53.10155 -0.7994084 480481
## 53 47046 23/06/1986 23 6 1986 53.10155 -0.7994084 480481
## 54 47046 23/06/1992 23 6 1992 53.10155 -0.7994084 480481
## 55 47046 25/05/2017 25 5 2017 53.10155 -0.7994084 480481
## 56 47046 25/06/1990 25 6 1990 53.10155 -0.7994084 480481
## 57 47046 26/02/1988 26 2 1988 53.10155 -0.7994084 480481
## 58 47046 26/02/1992 26 2 1992 53.10155 -0.7994084 480481
## 59 47046 26/10/2015 26 10 2015 53.10155 -0.7994084 480481
## 60 47046 27/01/1997 27 1 1997 53.10155 -0.7994084 480481
## 61 47046 27/03/1985 27 3 1985 53.10155 -0.7994084 480481
## 62 47046 27/10/2009 27 10 2009 53.10155 -0.7994084 480481
## 63 47046 28/03/1986 28 3 1986 53.10155 -0.7994084 480481
## 64 47046 29/03/1993 29 3 1993 53.10155 -0.7994084 480481
## 65 47046 29/09/2003 29 9 2003 53.10155 -0.7994084 480481
## 66 47046 29/11/1988 29 11 1988 53.10155 -0.7994084 480481
## 67 47046 31/03/2011 31 3 2011 53.10155 -0.7994084 480481
## 68 47046 31/10/2006 31 10 2006 53.10155 -0.7994084 480481
## 69 47046 31/10/2014 31 10 2014 53.10155 -0.7994084 480481
## 70 47078 01/10/1986 1 10 1986 52.57364 -1.1331985 458841
## 71 47078 02/05/1995 2 5 1995 52.57364 -1.1331985 458841
## 72 47078 02/06/1995 2 6 1995 52.57364 -1.1331985 458841
## 73 47078 03/04/1993 3 4 1993 52.57364 -1.1331985 458841
## 74 47078 04/03/1998 4 3 1998 52.57364 -1.1331985 458841
## 75 47078 04/04/1995 4 4 1995 52.57364 -1.1331985 458841
## 76 47078 04/05/1999 4 5 1999 52.57364 -1.1331985 458841
## 77 47078 04/12/1985 4 12 1985 52.57364 -1.1331985 458841
## 78 47078 05/01/1995 5 1 1995 52.57364 -1.1331985 458841
## 79 47078 05/12/1994 5 12 1994 52.57364 -1.1331985 458841
## 80 47078 06/03/1986 6 3 1986 52.57364 -1.1331985 458841
## 81 47078 06/11/1995 6 11 1995 52.57364 -1.1331985 458841
## 82 47078 06/11/2013 6 11 2013 52.57364 -1.1331985 458841
## 83 47078 07/02/1995 7 2 1995 52.57364 -1.1331985 458841
## 84 47078 07/03/1995 7 3 1995 52.57364 -1.1331985 458841
## 85 47078 07/05/2008 7 5 2008 52.57364 -1.1331985 458841
## 86 47078 07/09/1998 7 9 1998 52.57364 -1.1331985 458841
## 87 47078 08/03/1998 8 3 1998 52.57364 -1.1331985 458841
## 88 47078 08/11/1994 8 11 1994 52.57364 -1.1331985 458841
## 89 47078 09/02/1999 9 2 1999 52.57364 -1.1331985 458841
## 90 47078 10/04/2000 10 4 2000 52.57364 -1.1331985 458841
## 91 47078 10/10/1990 10 10 1990 52.57364 -1.1331985 458841
## 92 47078 10/12/1986 10 12 1986 52.57364 -1.1331985 458841
## 93 47078 11/01/2001 11 1 2001 52.57364 -1.1331985 458841
## 94 47078 11/07/1991 11 7 1991 52.57364 -1.1331985 458841
## 95 47078 11/09/1995 11 9 1995 52.57364 -1.1331985 458841
## 96 47078 11/10/1995 11 10 1995 52.57364 -1.1331985 458841
## 97 47078 12/03/1998 12 3 1998 52.57364 -1.1331985 458841
## 98 47078 12/04/1996 12 4 1996 52.57364 -1.1331985 458841
## 99 47078 12/04/2005 12 4 2005 52.57364 -1.1331985 458841
## 100 47078 12/05/1986 12 5 1986 52.57364 -1.1331985 458841
## 101 47078 12/05/1998 12 5 1998 52.57364 -1.1331985 458841
## 102 47078 13/06/1995 13 6 1995 52.57364 -1.1331985 458841
## 103 47078 13/08/1987 13 8 1987 52.57364 -1.1331985 458841
## 104 47078 13/08/1997 13 8 1997 52.57364 -1.1331985 458841
## 105 47078 13/09/1989 13 9 1989 52.57364 -1.1331985 458841
## 106 47078 13/09/2002 13 9 2002 52.57364 -1.1331985 458841
## 107 47078 14/05/1996 14 5 1996 52.57364 -1.1331985 458841
## 108 47078 14/10/1992 14 10 1992 52.57364 -1.1331985 458841
## 109 47078 15/04/1988 15 4 1988 52.57364 -1.1331985 458841
## 110 47078 15/04/1991 15 4 1991 52.57364 -1.1331985 458841
## 111 47078 15/11/1989 15 11 1989 52.57364 -1.1331985 458841
## 112 47078 16/02/1996 16 2 1996 52.57364 -1.1331985 458841
## 113 47078 16/04/1999 16 4 1999 52.57364 -1.1331985 458841
## 114 47078 16/04/2003 16 4 2003 52.57364 -1.1331985 458841
## 115 47078 16/05/2013 16 5 2013 52.57364 -1.1331985 458841
## 116 47078 17/01/1996 17 1 1996 52.57364 -1.1331985 458841
## 117 47078 17/06/1985 17 6 1985 52.57364 -1.1331985 458841
## 118 47078 17/06/1996 17 6 1996 52.57364 -1.1331985 458841
## 119 47078 17/08/1999 17 8 1999 52.57364 -1.1331985 458841
## 120 47078 17/12/1996 17 12 1996 52.57364 -1.1331985 458841
## 121 47078 18/04/1994 18 4 1994 52.57364 -1.1331985 458841
## 122 47078 18/11/1994 18 11 1994 52.57364 -1.1331985 458841
## 123 47078 19/03/1996 19 3 1996 52.57364 -1.1331985 458841
## 124 47078 19/04/1995 19 4 1995 52.57364 -1.1331985 458841
## 125 47078 19/05/1995 19 5 1995 52.57364 -1.1331985 458841
## 126 47078 20/04/1998 20 4 1998 52.57364 -1.1331985 458841
## 127 47078 20/05/2014 20 5 2014 52.57364 -1.1331985 458841
## 128 47078 20/06/2000 20 6 2000 52.57364 -1.1331985 458841
## 129 47078 20/07/1993 20 7 1993 52.57364 -1.1331985 458841
## 130 47078 20/11/1998 20 11 1998 52.57364 -1.1331985 458841
## 131 47078 20/12/1995 20 12 1995 52.57364 -1.1331985 458841
## 132 47078 21/02/1995 21 2 1995 52.57364 -1.1331985 458841
## 133 47078 21/11/2008 21 11 2008 52.57364 -1.1331985 458841
## 134 47078 21/12/1994 21 12 1994 52.57364 -1.1331985 458841
## 135 47078 22/02/1988 22 2 1988 52.57364 -1.1331985 458841
## 136 47078 22/03/1995 22 3 1995 52.57364 -1.1331985 458841
## 137 47078 22/05/1989 22 5 1989 52.57364 -1.1331985 458841
## 138 47078 22/05/2012 22 5 2012 52.57364 -1.1331985 458841
## 139 47078 22/08/2000 22 8 2000 52.57364 -1.1331985 458841
## 140 47078 22/11/1988 22 11 1988 52.57364 -1.1331985 458841
## 141 47078 22/12/2000 22 12 2000 52.57364 -1.1331985 458841
## 142 47078 23/04/1996 23 4 1996 52.57364 -1.1331985 458841
## 143 47078 23/10/2000 23 10 2000 52.57364 -1.1331985 458841
## 144 47078 24/01/1995 24 1 1995 52.57364 -1.1331985 458841
## 145 47078 24/04/2002 24 4 2002 52.57364 -1.1331985 458841
## 146 47078 24/05/1999 24 5 1999 52.57364 -1.1331985 458841
## 147 47078 24/09/2014 24 9 2014 52.57364 -1.1331985 458841
## 148 47078 24/10/1994 24 10 1994 52.57364 -1.1331985 458841
## 149 47078 25/02/1985 25 2 1985 52.57364 -1.1331985 458841
## 150 47078 25/03/1992 25 3 1992 52.57364 -1.1331985 458841
## 151 47078 25/07/1995 25 7 1995 52.57364 -1.1331985 458841
## 152 47078 25/10/1995 25 10 1995 52.57364 -1.1331985 458841
## 153 47078 25/11/1997 25 11 1997 52.57364 -1.1331985 458841
## 154 47078 25/11/1999 25 11 1999 52.57364 -1.1331985 458841
## 155 47078 26/01/2000 26 1 2000 52.57364 -1.1331985 458841
## 156 47078 26/03/1998 26 3 1998 52.57364 -1.1331985 458841
## 157 47078 26/07/1994 26 7 1994 52.57364 -1.1331985 458841
## 158 47078 26/11/1987 26 11 1987 52.57364 -1.1331985 458841
## 159 47078 27/10/1993 27 10 1993 52.57364 -1.1331985 458841
## 160 47078 28/02/1996 28 2 1996 52.57364 -1.1331985 458841
## 161 47078 28/04/1998 28 4 1998 52.57364 -1.1331985 458841
## 162 47078 28/09/1990 28 9 1990 52.57364 -1.1331985 458841
## 163 47078 28/09/1995 28 9 1995 52.57364 -1.1331985 458841
## 164 47078 28/09/2005 28 9 2005 52.57364 -1.1331985 458841
## 165 47078 28/10/1991 28 10 1991 52.57364 -1.1331985 458841
## 166 47078 29/05/2001 29 5 2001 52.57364 -1.1331985 458841
## 167 47078 29/06/1995 29 6 1995 52.57364 -1.1331985 458841
## 168 47078 29/09/1998 29 9 1998 52.57364 -1.1331985 458841
## 169 47078 29/09/2000 29 9 2000 52.57364 -1.1331985 458841
## 170 47078 29/11/1995 29 11 1995 52.57364 -1.1331985 458841
## 171 47078 30/04/1987 30 4 1987 52.57364 -1.1331985 458841
## 172 47078 30/04/1998 30 4 1998 52.57364 -1.1331985 458841
## 173 47078 30/09/1999 30 9 1999 52.57364 -1.1331985 458841
## 174 47078 31/03/1998 31 3 1998 52.57364 -1.1331985 458841
## 175 47078 31/05/2000 31 5 2000 52.57364 -1.1331985 458841
## 176 47078 31/07/2000 31 7 2000 52.57364 -1.1331985 458841
## 177 47138 01/11/2001 1 11 2001 53.08520 -1.5069310 433123
## 178 47138 02/05/2013 2 5 2013 53.08520 -1.5069310 433123
## 179 47138 03/04/2009 3 4 2009 53.08520 -1.5069310 433123
## 180 47138 03/10/2011 3 10 2011 53.08520 -1.5069310 433123
## 181 47138 03/12/1991 3 12 1991 53.08520 -1.5069310 433123
## 182 47138 04/03/1987 4 3 1987 53.08520 -1.5069310 433123
## 183 47138 04/04/2017 4 4 2017 53.08520 -1.5069310 433123
## 184 47138 04/10/2005 4 10 2005 53.08520 -1.5069310 433123
## 185 47138 05/06/1986 5 6 1986 53.08520 -1.5069310 433123
## 186 47138 05/11/2003 5 11 2003 53.08520 -1.5069310 433123
## 187 47138 05/11/2004 5 11 2004 53.08520 -1.5069310 433123
## 188 47138 06/09/1995 6 9 1995 53.08520 -1.5069310 433123
## 189 47138 07/01/1993 7 1 1993 53.08520 -1.5069310 433123
## 190 47138 07/10/2013 7 10 2013 53.08520 -1.5069310 433123
## 191 47138 08/05/2007 8 5 2007 53.08520 -1.5069310 433123
## 192 47138 08/05/2015 8 5 2015 53.08520 -1.5069310 433123
## 193 47138 08/07/1987 8 7 1987 53.08520 -1.5069310 433123
## 194 47138 08/08/1991 8 8 1991 53.08520 -1.5069310 433123
## 195 47138 08/10/2014 8 10 2014 53.08520 -1.5069310 433123
## 196 47138 08/11/2017 8 11 2017 53.08520 -1.5069310 433123
## 197 47138 10/01/1989 10 1 1989 53.08520 -1.5069310 433123
## 198 47138 10/05/1985 10 5 1985 53.08520 -1.5069310 433123
## 199 47138 10/09/1985 10 9 1985 53.08520 -1.5069310 433123
## 200 47138 11/04/2008 11 4 2008 53.08520 -1.5069310 433123
## 201 47138 11/05/1987 11 5 1987 53.08520 -1.5069310 433123
## 202 47138 11/05/1992 11 5 1992 53.08520 -1.5069310 433123
## 203 47138 11/05/2004 11 5 2004 53.08520 -1.5069310 433123
## 204 47138 12/03/1997 12 3 1997 53.08520 -1.5069310 433123
## 205 47138 12/04/2005 12 4 2005 53.08520 -1.5069310 433123
## 206 47138 13/05/1991 13 5 1991 53.08520 -1.5069310 433123
## 207 47138 13/09/2000 13 9 2000 53.08520 -1.5069310 433123
## 208 47138 14/04/2011 14 4 2011 53.08520 -1.5069310 433123
## 209 47138 14/10/1996 14 10 1996 53.08520 -1.5069310 433123
## 210 47138 15/04/2014 15 4 2014 53.08520 -1.5069310 433123
## 211 47138 15/08/1990 15 8 1990 53.08520 -1.5069310 433123
## 212 47138 15/10/2009 15 10 2009 53.08520 -1.5069310 433123
## 213 47138 15/11/1988 15 11 1988 53.08520 -1.5069310 433123
## 214 47138 16/05/2006 16 5 2006 53.08520 -1.5069310 433123
## 215 47138 16/10/2015 16 10 2015 53.08520 -1.5069310 433123
## 216 47138 16/11/2018 16 11 2018 53.08520 -1.5069310 433123
## 217 47138 17/04/1989 17 4 1989 53.08520 -1.5069310 433123
## 218 47138 17/04/2018 17 4 2018 53.08520 -1.5069310 433123
## 219 47138 17/05/1988 17 5 1988 53.08520 -1.5069310 433123
## 220 47138 17/05/1990 17 5 1990 53.08520 -1.5069310 433123
## 221 47138 17/09/1987 17 9 1987 53.08520 -1.5069310 433123
## 222 47138 17/09/1999 17 9 1999 53.08520 -1.5069310 433123
## 223 47138 18/04/2002 18 4 2002 53.08520 -1.5069310 433123
## 224 47138 18/05/2016 18 5 2016 53.08520 -1.5069310 433123
## 225 47138 19/05/1994 19 5 1994 53.08520 -1.5069310 433123
## 226 47138 19/06/1986 19 6 1986 53.08520 -1.5069310 433123
## 227 47138 19/08/1986 19 8 1986 53.08520 -1.5069310 433123
## 228 47138 19/09/2002 19 9 2002 53.08520 -1.5069310 433123
## 229 47138 19/09/2012 19 9 2012 53.08520 -1.5069310 433123
## 230 47138 19/11/1987 19 11 1987 53.08520 -1.5069310 433123
## 231 47138 20/03/1998 20 3 1998 53.08520 -1.5069310 433123
## 232 47138 20/09/2007 20 9 2007 53.08520 -1.5069310 433123
## 233 47138 22/04/1993 22 4 1993 53.08520 -1.5069310 433123
## 234 47138 22/05/2012 22 5 2012 53.08520 -1.5069310 433123
## 235 47138 22/06/1989 22 6 1989 53.08520 -1.5069310 433123
## 236 47138 23/02/1989 23 2 1989 53.08520 -1.5069310 433123
## 237 47138 23/07/1997 23 7 1997 53.08520 -1.5069310 433123
## 238 47138 23/08/1994 23 8 1994 53.08520 -1.5069310 433123
## 239 47138 23/09/2010 23 9 2010 53.08520 -1.5069310 433123
## 240 47138 23/10/1989 23 10 1989 53.08520 -1.5069310 433123
## 241 47138 24/05/2000 24 5 2000 53.08520 -1.5069310 433123
## 242 47138 24/11/1993 24 11 1993 53.08520 -1.5069310 433123
## 243 47138 24/11/1998 24 11 1998 53.08520 -1.5069310 433123
## 244 47138 24/11/2006 24 11 2006 53.08520 -1.5069310 433123
## 245 47138 25/06/1987 25 6 1987 53.08520 -1.5069310 433123
## 246 47138 25/08/1987 25 8 1987 53.08520 -1.5069310 433123
## 247 47138 25/09/1997 25 9 1997 53.08520 -1.5069310 433123
## 248 47138 25/09/2008 25 9 2008 53.08520 -1.5069310 433123
## 249 47138 25/11/1987 25 11 1987 53.08520 -1.5069310 433123
## 250 47138 26/04/1995 26 4 1995 53.08520 -1.5069310 433123
## 251 47138 26/09/1985 26 9 1985 53.08520 -1.5069310 433123
## 252 47138 27/10/2016 27 10 2016 53.08520 -1.5069310 433123
## 253 47138 28/03/1996 28 3 1996 53.08520 -1.5069310 433123
## 254 47138 28/07/1987 28 7 1987 53.08520 -1.5069310 433123
## 255 47138 28/11/1990 28 11 1990 53.08520 -1.5069310 433123
## 256 47138 29/04/2010 29 4 2010 53.08520 -1.5069310 433123
## 257 47138 29/07/1992 29 7 1992 53.08520 -1.5069310 433123
## 258 47138 30/04/2003 30 4 2003 53.08520 -1.5069310 433123
## 259 47138 31/08/1993 31 8 1993 53.08520 -1.5069310 433123
## 260 47157 01/05/1985 1 5 1985 53.10189 -1.8590422 409535
## 261 47157 02/12/1987 2 12 1987 53.10189 -1.8590422 409535
## 262 47157 03/09/2004 3 9 2004 53.10189 -1.8590422 409535
## 263 47157 04/03/1991 4 3 1991 53.10189 -1.8590422 409535
## 264 47157 04/10/2005 4 10 2005 53.10189 -1.8590422 409535
## 265 47157 06/09/1989 6 9 1989 53.10189 -1.8590422 409535
## 266 47157 06/10/1999 6 10 1999 53.10189 -1.8590422 409535
## 267 47157 08/03/1995 8 3 1995 53.10189 -1.8590422 409535
## 268 47157 08/10/1990 8 10 1990 53.10189 -1.8590422 409535
## 269 47157 09/05/1994 9 5 1994 53.10189 -1.8590422 409535
## 270 47157 12/08/1986 12 8 1986 53.10189 -1.8590422 409535
## 271 47157 13/02/1992 13 2 1992 53.10189 -1.8590422 409535
## 272 47157 13/03/2000 13 3 2000 53.10189 -1.8590422 409535
## 273 47157 13/09/1995 13 9 1995 53.10189 -1.8590422 409535
## 274 47157 13/09/2002 13 9 2002 53.10189 -1.8590422 409535
## 275 47157 13/10/1991 13 10 1991 53.10189 -1.8590422 409535
## 276 47157 14/04/1993 14 4 1993 53.10189 -1.8590422 409535
## 277 47157 14/10/2008 14 10 2008 53.10189 -1.8590422 409535
## 278 47157 14/11/1983 14 11 1983 53.10189 -1.8590422 409535
## 279 47157 15/07/1993 15 7 1993 53.10189 -1.8590422 409535
## 280 47157 16/03/1999 16 3 1999 53.10189 -1.8590422 409535
## 281 47157 16/05/2008 16 5 2008 53.10189 -1.8590422 409535
## 282 47157 16/05/2012 16 5 2012 53.10189 -1.8590422 409535
## 283 47157 17/03/1987 17 3 1987 53.10189 -1.8590422 409535
## 284 47157 17/03/2004 17 3 2004 53.10189 -1.8590422 409535
## 285 47157 17/04/2003 17 4 2003 53.10189 -1.8590422 409535
## 286 47157 17/06/1997 17 6 1997 53.10189 -1.8590422 409535
## 287 47157 17/07/1991 17 7 1991 53.10189 -1.8590422 409535
## 288 47157 18/10/2000 18 10 2000 53.10189 -1.8590422 409535
## 289 47157 18/11/1998 18 11 1998 53.10189 -1.8590422 409535
## 290 47157 19/06/1990 19 6 1990 53.10189 -1.8590422 409535
## 291 47157 20/03/1990 20 3 1990 53.10189 -1.8590422 409535
## 292 47157 20/04/2007 20 4 2007 53.10189 -1.8590422 409535
## 293 47157 20/05/1996 20 5 1996 53.10189 -1.8590422 409535
## 294 47157 20/09/2001 20 9 2001 53.10189 -1.8590422 409535
## 295 47157 20/09/2006 20 9 2006 53.10189 -1.8590422 409535
## 296 47157 20/09/2012 20 9 2012 53.10189 -1.8590422 409535
## 297 47157 21/06/1988 21 6 1988 53.10189 -1.8590422 409535
## 298 47157 22/04/1998 22 4 1998 53.10189 -1.8590422 409535
## 299 47157 22/08/1994 22 8 1994 53.10189 -1.8590422 409535
## 300 47157 22/11/1993 22 11 1993 53.10189 -1.8590422 409535
## 301 47157 23/04/2002 23 4 2002 53.10189 -1.8590422 409535
## 302 47157 23/10/1996 23 10 1996 53.10189 -1.8590422 409535
## 303 47157 24/04/1985 24 4 1985 53.10189 -1.8590422 409535
## 304 47157 24/06/1992 24 6 1992 53.10189 -1.8590422 409535
## 305 47157 24/09/2003 24 9 2003 53.10189 -1.8590422 409535
## 306 47157 25/11/1985 25 11 1985 53.10189 -1.8590422 409535
## 307 47157 26/10/1987 26 10 1987 53.10189 -1.8590422 409535
## 308 47157 28/04/2005 28 4 2005 53.10189 -1.8590422 409535
## 309 47157 28/10/1997 28 10 1997 53.10189 -1.8590422 409535
## 310 47157 31/10/1992 31 10 1992 53.10189 -1.8590422 409535
## 311 47255 02/05/1995 2 5 1995 52.52080 -1.7521412 416915
## 312 47255 02/08/1990 2 8 1990 52.52080 -1.7521412 416915
## 313 47255 03/01/1997 3 1 1997 52.52080 -1.7521412 416915
## 314 47255 03/10/1995 3 10 1995 52.52080 -1.7521412 416915
## 315 47255 04/12/1998 4 12 1998 52.52080 -1.7521412 416915
## 316 47255 06/04/2004 6 4 2004 52.52080 -1.7521412 416915
## 317 47255 07/04/2000 7 4 2000 52.52080 -1.7521412 416915
## 318 47255 07/09/2000 7 9 2000 52.52080 -1.7521412 416915
## 319 47255 07/11/1994 7 11 1994 52.52080 -1.7521412 416915
## 320 47255 08/09/2011 8 9 2011 52.52080 -1.7521412 416915
## 321 47255 08/10/2002 8 10 2002 52.52080 -1.7521412 416915
## 322 47255 08/10/2018 8 10 2018 52.52080 -1.7521412 416915
## 323 47255 09/04/2003 9 4 2003 52.52080 -1.7521412 416915
## 324 47255 09/09/2015 9 9 2015 52.52080 -1.7521412 416915
## 325 47255 10/07/1994 10 7 1994 52.52080 -1.7521412 416915
## 326 47255 10/10/2003 10 10 2003 52.52080 -1.7521412 416915
## 327 47255 11/09/2001 11 9 2001 52.52080 -1.7521412 416915
## 328 47255 12/06/1989 12 6 1989 52.52080 -1.7521412 416915
## 329 47255 13/08/1992 13 8 1992 52.52080 -1.7521412 416915
## 330 47255 14/11/1997 14 11 1997 52.52080 -1.7521412 416915
## 331 47255 15/05/1988 15 5 1988 52.52080 -1.7521412 416915
## 332 47255 16/12/1992 16 12 1992 52.52080 -1.7521412 416915
## 333 47255 17/03/1993 17 3 1993 52.52080 -1.7521412 416915
## 334 47255 17/11/2008 17 11 2008 52.52080 -1.7521412 416915
## 335 47255 18/04/2002 18 4 2002 52.52080 -1.7521412 416915
## 336 47255 18/05/2001 18 5 2001 52.52080 -1.7521412 416915
## 337 47255 19/01/1987 19 1 1987 52.52080 -1.7521412 416915
## 338 47255 19/03/2010 19 3 2010 52.52080 -1.7521412 416915
## 339 47255 19/04/2011 19 4 2011 52.52080 -1.7521412 416915
## 340 47255 19/09/1988 19 9 1988 52.52080 -1.7521412 416915
## 341 47255 19/10/1999 19 10 1999 52.52080 -1.7521412 416915
## 342 47255 19/12/2001 19 12 2001 52.52080 -1.7521412 416915
## 343 47255 20/03/2007 20 3 2007 52.52080 -1.7521412 416915
## 344 47255 20/06/2002 20 6 2002 52.52080 -1.7521412 416915
## 345 47255 21/03/1994 21 3 1994 52.52080 -1.7521412 416915
## 346 47255 21/03/2006 21 3 2006 52.52080 -1.7521412 416915
## 347 47255 21/05/1999 21 5 1999 52.52080 -1.7521412 416915
## 348 47255 21/06/1993 21 6 1993 52.52080 -1.7521412 416915
## 349 47255 21/09/2006 21 9 2006 52.52080 -1.7521412 416915
## 350 47255 21/09/2010 21 9 2010 52.52080 -1.7521412 416915
## 351 47255 21/10/2009 21 10 2009 52.52080 -1.7521412 416915
## 352 47255 22/05/2018 22 5 2018 52.52080 -1.7521412 416915
## 353 47255 22/06/1998 22 6 1998 52.52080 -1.7521412 416915
## 354 47255 23/11/1987 23 11 1987 52.52080 -1.7521412 416915
## 355 47255 23/11/2007 23 11 2007 52.52080 -1.7521412 416915
## 356 47255 24/01/2003 24 1 2003 52.52080 -1.7521412 416915
## 357 47255 24/03/2005 24 3 2005 52.52080 -1.7521412 416915
## 358 47255 24/07/1996 24 7 1996 52.52080 -1.7521412 416915
## 359 47255 24/08/1989 24 8 1989 52.52080 -1.7521412 416915
## 360 47255 25/04/2008 25 4 2008 52.52080 -1.7521412 416915
## 361 47255 26/06/1987 26 6 1987 52.52080 -1.7521412 416915
## 362 47255 26/10/1993 26 10 1993 52.52080 -1.7521412 416915
## 363 47255 26/11/1987 26 11 1987 52.52080 -1.7521412 416915
## 364 47255 26/11/1990 26 11 1990 52.52080 -1.7521412 416915
## 365 47255 27/09/2005 27 9 2005 52.52080 -1.7521412 416915
## 366 47255 27/11/1989 27 11 1989 52.52080 -1.7521412 416915
## 367 47255 29/10/1991 29 10 1991 52.52080 -1.7521412 416915
## 368 47255 30/04/2015 30 4 2015 52.52080 -1.7521412 416915
## 369 47255 30/10/2012 30 10 2012 52.52080 -1.7521412 416915
## 370 47255 31/05/1990 31 5 1990 52.52080 -1.7521412 416915
## 371 47310 01/09/2017 1 9 2017 53.09501 -2.0403088 397398
## 372 47310 02/09/2010 2 9 2010 53.09501 -2.0403088 397398
## 373 47310 02/12/1993 2 12 1993 53.09501 -2.0403088 397398
## 374 47310 03/06/1985 3 6 1985 53.09501 -2.0403088 397398
## 375 47310 03/08/2011 3 8 2011 53.09501 -2.0403088 397398
## 376 47310 04/06/1997 4 6 1997 53.09501 -2.0403088 397398
## 377 47310 04/09/1989 4 9 1989 53.09501 -2.0403088 397398
## 378 47310 05/10/2018 5 10 2018 53.09501 -2.0403088 397398
## 379 47310 06/09/1994 6 9 1994 53.09501 -2.0403088 397398
## 380 47310 06/09/2013 6 9 2013 53.09501 -2.0403088 397398
## 381 47310 07/04/2006 7 4 2006 53.09501 -2.0403088 397398
## 382 47310 07/05/2013 7 5 2013 53.09501 -2.0403088 397398
## 383 47310 07/12/1987 7 12 1987 53.09501 -2.0403088 397398
## 384 47310 08/03/1995 8 3 1995 53.09501 -2.0403088 397398
## 385 47310 08/05/1991 8 5 1991 53.09501 -2.0403088 397398
## 386 47310 08/10/1985 8 10 1985 53.09501 -2.0403088 397398
## 387 47310 08/10/1998 8 10 1998 53.09501 -2.0403088 397398
## 388 47310 08/10/2009 8 10 2009 53.09501 -2.0403088 397398
## 389 47310 09/04/2009 9 4 2009 53.09501 -2.0403088 397398
## 390 47310 09/11/2011 9 11 2011 53.09501 -2.0403088 397398
## 391 47310 10/08/1993 10 8 1993 53.09501 -2.0403088 397398
## 392 47310 11/05/1993 11 5 1993 53.09501 -2.0403088 397398
## 393 47310 11/09/1995 11 9 1995 53.09501 -2.0403088 397398
## 394 47310 11/09/2002 11 9 2002 53.09501 -2.0403088 397398
## 395 47310 12/03/1985 12 3 1985 53.09501 -2.0403088 397398
## 396 47310 12/04/1994 12 4 1994 53.09501 -2.0403088 397398
## 397 47310 12/05/2016 12 5 2016 53.09501 -2.0403088 397398
## 398 47310 12/07/1988 12 7 1988 53.09501 -2.0403088 397398
## 399 47310 13/01/1993 13 1 1993 53.09501 -2.0403088 397398
## 400 47310 13/05/1986 13 5 1986 53.09501 -2.0403088 397398
## 401 47310 13/05/2014 13 5 2014 53.09501 -2.0403088 397398
## 402 47310 13/06/1991 13 6 1991 53.09501 -2.0403088 397398
## 403 47310 13/08/1985 13 8 1985 53.09501 -2.0403088 397398
## 404 47310 13/10/2004 13 10 2004 53.09501 -2.0403088 397398
## 405 47310 13/10/2006 13 10 2006 53.09501 -2.0403088 397398
## 406 47310 14/10/2005 14 10 2005 53.09501 -2.0403088 397398
## 407 47310 14/12/2001 14 12 2001 53.09501 -2.0403088 397398
## 408 47310 15/07/1992 15 7 1992 53.09501 -2.0403088 397398
## 409 47310 16/04/2002 16 4 2002 53.09501 -2.0403088 397398
## 410 47310 16/04/2003 16 4 2003 53.09501 -2.0403088 397398
## 411 47310 18/03/1996 18 3 1996 53.09501 -2.0403088 397398
## 412 47310 18/05/2000 18 5 2000 53.09501 -2.0403088 397398
## 413 47310 19/03/2012 19 3 2012 53.09501 -2.0403088 397398
## 414 47310 19/09/2003 19 9 2003 53.09501 -2.0403088 397398
## 415 47310 19/09/2008 19 9 2008 53.09501 -2.0403088 397398
## 416 47310 19/12/1985 19 12 1985 53.09501 -2.0403088 397398
## 417 47310 20/03/1990 20 3 1990 53.09501 -2.0403088 397398
## 418 47310 20/04/2007 20 4 2007 53.09501 -2.0403088 397398
## 419 47310 20/05/1998 20 5 1998 53.09501 -2.0403088 397398
## 420 47310 20/06/1990 20 6 1990 53.09501 -2.0403088 397398
## 421 47310 20/10/2016 20 10 2016 53.09501 -2.0403088 397398
## 422 47310 21/03/2005 21 3 2005 53.09501 -2.0403088 397398
## 423 47310 22/03/2011 22 3 2011 53.09501 -2.0403088 397398
## 424 47310 22/05/2017 22 5 2017 53.09501 -2.0403088 397398
## 425 47310 22/09/2000 22 9 2000 53.09501 -2.0403088 397398
## 426 47310 22/10/1986 22 10 1986 53.09501 -2.0403088 397398
## 427 47310 23/05/2018 23 5 2018 53.09501 -2.0403088 397398
## 428 47310 23/09/2015 23 9 2015 53.09501 -2.0403088 397398
## 429 47310 24/09/2014 24 9 2014 53.09501 -2.0403088 397398
## 430 47310 25/03/2004 25 3 2004 53.09501 -2.0403088 397398
## 431 47310 25/04/2008 25 4 2008 53.09501 -2.0403088 397398
## 432 47310 26/05/1999 26 5 1999 53.09501 -2.0403088 397398
## 433 47310 26/09/1990 26 9 1990 53.09501 -2.0403088 397398
## 434 47310 26/11/1991 26 11 1991 53.09501 -2.0403088 397398
## 435 47310 27/04/1987 27 4 1987 53.09501 -2.0403088 397398
## 436 47310 27/04/2010 27 4 2010 53.09501 -2.0403088 397398
## 437 47310 27/04/2015 27 4 2015 53.09501 -2.0403088 397398
## 438 47310 27/09/2007 27 9 2007 53.09501 -2.0403088 397398
## 439 47310 27/11/1996 27 11 1996 53.09501 -2.0403088 397398
## 440 47310 30/08/2012 30 8 2012 53.09501 -2.0403088 397398
## 441 47310 31/10/1997 31 10 1997 53.09501 -2.0403088 397398
## 442 47348 01/07/1992 1 7 1992 51.75741 -2.5549722 361791
## 443 47348 01/11/2011 1 11 2011 51.75741 -2.5549722 361791
## 444 47348 01/11/2018 1 11 2018 51.75741 -2.5549722 361791
## 445 47348 02/04/2008 2 4 2008 51.75741 -2.5549722 361791
## 446 47348 03/11/2010 3 11 2010 51.75741 -2.5549722 361791
## 447 47348 04/07/1991 4 7 1991 51.75741 -2.5549722 361791
## 448 47348 04/11/2003 4 11 2003 51.75741 -2.5549722 361791
## 449 47348 06/10/2016 6 10 2016 51.75741 -2.5549722 361791
## 450 47348 07/04/2010 7 4 2010 51.75741 -2.5549722 361791
## 451 47348 07/05/1998 7 5 1998 51.75741 -2.5549722 361791
## 452 47348 08/09/2009 8 9 2009 51.75741 -2.5549722 361791
## 453 47348 08/11/2012 8 11 2012 51.75741 -2.5549722 361791
## 454 47348 09/10/2006 9 10 2006 51.75741 -2.5549722 361791
## 455 47348 09/10/2013 9 10 2013 51.75741 -2.5549722 361791
## 456 47348 09/12/1997 9 12 1997 51.75741 -2.5549722 361791
## 457 47348 10/03/2009 10 3 2009 51.75741 -2.5549722 361791
## 458 47348 10/12/1996 10 12 1996 51.75741 -2.5549722 361791
## 459 47348 11/04/1995 11 4 1995 51.75741 -2.5549722 361791
## 460 47348 12/03/2015 12 3 2015 51.75741 -2.5549722 361791
## 461 47348 12/04/1990 12 4 1990 51.75741 -2.5549722 361791
## 462 47348 12/04/2017 12 4 2017 51.75741 -2.5549722 361791
## 463 47348 12/07/1993 12 7 1993 51.75741 -2.5549722 361791
## 464 47348 13/03/2000 13 3 2000 51.75741 -2.5549722 361791
## 465 47348 13/05/2016 13 5 2016 51.75741 -2.5549722 361791
## 466 47348 14/04/1994 14 4 1994 51.75741 -2.5549722 361791
## 467 47348 14/10/2008 14 10 2008 51.75741 -2.5549722 361791
## 468 47348 14/11/1989 14 11 1989 51.75741 -2.5549722 361791
## 469 47348 14/11/1995 14 11 1995 51.75741 -2.5549722 361791
## 470 47348 15/04/1991 15 4 1991 51.75741 -2.5549722 361791
## 471 47348 15/11/2000 15 11 2000 51.75741 -2.5549722 361791
## 472 47348 16/10/2017 16 10 2017 51.75741 -2.5549722 361791
## 473 47348 17/05/2018 17 5 2018 51.75741 -2.5549722 361791
## 474 47348 17/09/2015 17 9 2015 51.75741 -2.5549722 361791
## 475 47348 18/07/1990 18 7 1990 51.75741 -2.5549722 361791
## 476 47348 19/04/2006 19 4 2006 51.75741 -2.5549722 361791
## 477 47348 19/04/2011 19 4 2011 51.75741 -2.5549722 361791
## 478 47348 19/04/2012 19 4 2012 51.75741 -2.5549722 361791
## 479 47348 20/11/1991 20 11 1991 51.75741 -2.5549722 361791
## 480 47348 21/08/1989 21 8 1989 51.75741 -2.5549722 361791
## 481 47348 21/11/1994 21 11 1994 51.75741 -2.5549722 361791
## 482 47348 22/04/2013 22 4 2013 51.75741 -2.5549722 361791
## 483 47348 22/10/1998 22 10 1998 51.75741 -2.5549722 361791
## 484 47348 22/11/1993 22 11 1993 51.75741 -2.5549722 361791
## 485 47348 23/02/1993 23 2 1993 51.75741 -2.5549722 361791
## 486 47348 23/04/1992 23 4 1992 51.75741 -2.5549722 361791
## 487 47348 23/10/1990 23 10 1990 51.75741 -2.5549722 361791
## 488 47348 24/04/1997 24 4 1997 51.75741 -2.5549722 361791
## 489 47348 24/04/2014 24 4 2014 51.75741 -2.5549722 361791
## 490 47348 27/03/2002 27 3 2002 51.75741 -2.5549722 361791
## 491 47348 27/10/2014 27 10 2014 51.75741 -2.5549722 361791
## 492 47348 28/06/1993 28 6 1993 51.75741 -2.5549722 361791
## 493 47348 29/04/2003 29 4 2003 51.75741 -2.5549722 361791
## 494 48226 01/07/1985 1 7 1985 52.38165 -1.7016913 420402
## 495 48226 02/11/1994 2 11 1994 52.38165 -1.7016913 420402
## 496 48226 03/04/1991 3 4 1991 52.38165 -1.7016913 420402
## 497 48226 03/04/2014 3 4 2014 52.38165 -1.7016913 420402
## 498 48226 03/06/1996 3 6 1996 52.38165 -1.7016913 420402
## 499 48226 05/05/2011 5 5 2011 52.38165 -1.7016913 420402
## 500 48226 07/08/1990 7 8 1990 52.38165 -1.7016913 420402
## 501 48226 07/09/1987 7 9 1987 52.38165 -1.7016913 420402
## 502 48226 07/12/2001 7 12 2001 52.38165 -1.7016913 420402
## 503 48226 08/02/1988 8 2 1988 52.38165 -1.7016913 420402
## 504 48226 08/03/1994 8 3 1994 52.38165 -1.7016913 420402
## 505 48226 08/09/1982 8 9 1982 52.38165 -1.7016913 420402
## 506 48226 09/07/1992 9 7 1992 52.38165 -1.7016913 420402
## 507 48226 09/09/2014 9 9 2014 52.38165 -1.7016913 420402
## 508 48226 10/06/1997 10 6 1997 52.38165 -1.7016913 420402
## 509 48226 11/10/1993 11 10 1993 52.38165 -1.7016913 420402
## 510 48226 12/03/2003 12 3 2003 52.38165 -1.7016913 420402
## 511 48226 12/09/2011 12 9 2011 52.38165 -1.7016913 420402
## 512 48226 13/05/1988 13 5 1988 52.38165 -1.7016913 420402
## 513 48226 13/11/1995 13 11 1995 52.38165 -1.7016913 420402
## 514 48226 14/11/2012 14 11 2012 52.38165 -1.7016913 420402
## 515 48226 16/03/2006 16 3 2006 52.38165 -1.7016913 420402
## 516 48226 16/05/1990 16 5 1990 52.38165 -1.7016913 420402
## 517 48226 16/05/1995 16 5 1995 52.38165 -1.7016913 420402
## 518 48226 16/06/1999 16 6 1999 52.38165 -1.7016913 420402
## 519 48226 16/09/1996 16 9 1996 52.38165 -1.7016913 420402
## 520 48226 17/03/1987 17 3 1987 52.38165 -1.7016913 420402
## 521 48226 17/05/1993 17 5 1993 52.38165 -1.7016913 420402
## 522 48226 18/02/1985 18 2 1985 52.38165 -1.7016913 420402
## 523 48226 18/07/1988 18 7 1988 52.38165 -1.7016913 420402
## 524 48226 18/11/1985 18 11 1985 52.38165 -1.7016913 420402
## 525 48226 20/03/2000 20 3 2000 52.38165 -1.7016913 420402
## 526 48226 20/04/2010 20 4 2010 52.38165 -1.7016913 420402
## 527 48226 20/06/1994 20 6 1994 52.38165 -1.7016913 420402
## 528 48226 21/01/1998 21 1 1998 52.38165 -1.7016913 420402
## 529 48226 21/09/2006 21 9 2006 52.38165 -1.7016913 420402
## 530 48226 21/10/2003 21 10 2003 52.38165 -1.7016913 420402
## 531 48226 21/11/1988 21 11 1988 52.38165 -1.7016913 420402
## 532 48226 21/11/1990 21 11 1990 52.38165 -1.7016913 420402
## 533 48226 22/02/1993 22 2 1993 52.38165 -1.7016913 420402
## 534 48226 22/10/1992 22 10 1992 52.38165 -1.7016913 420402
## 535 48226 22/11/2010 22 11 2010 52.38165 -1.7016913 420402
## 536 48226 22/12/2000 22 12 2000 52.38165 -1.7016913 420402
## 537 48226 23/05/1989 23 5 1989 52.38165 -1.7016913 420402
## 538 48226 24/05/2012 24 5 2012 52.38165 -1.7016913 420402
## 539 48226 26/05/1998 26 5 1998 52.38165 -1.7016913 420402
## 540 48226 27/05/2009 27 5 2009 52.38165 -1.7016913 420402
## 541 48226 28/04/1986 28 4 1986 52.38165 -1.7016913 420402
## 542 48226 28/10/1991 28 10 1991 52.38165 -1.7016913 420402
## 543 48226 29/09/1986 29 9 1986 52.38165 -1.7016913 420402
## 544 48226 30/03/1992 30 3 1992 52.38165 -1.7016913 420402
## 545 48226 30/10/1989 30 10 1989 52.38165 -1.7016913 420402
## 546 48226 30/11/1998 30 11 1998 52.38165 -1.7016913 420402
## 547 48583 01/07/1997 1 7 1997 53.09529 -1.4321933 438120
## 548 48583 02/10/2002 2 10 2002 53.09529 -1.4321933 438120
## 549 48583 03/04/2002 3 4 2002 53.09529 -1.4321933 438120
## 550 48583 03/06/1986 3 6 1986 53.09529 -1.4321933 438120
## 551 48583 03/09/1986 3 9 1986 53.09529 -1.4321933 438120
## 552 48583 03/10/1994 3 10 1994 53.09529 -1.4321933 438120
## 553 48583 05/03/1985 5 3 1985 53.09529 -1.4321933 438120
## 554 48583 06/03/1990 6 3 1990 53.09529 -1.4321933 438120
## 555 48583 08/03/1995 8 3 1995 53.09529 -1.4321933 438120
## 556 48583 08/05/2018 8 5 2018 53.09529 -1.4321933 438120
## 557 48583 09/04/2003 9 4 2003 53.09529 -1.4321933 438120
## 558 48583 10/01/1989 10 1 1989 53.09529 -1.4321933 438120
## 559 48583 11/03/1991 11 3 1991 53.09529 -1.4321933 438120
## 560 48583 11/06/1991 11 6 1991 53.09529 -1.4321933 438120
## 561 48583 11/12/1996 11 12 1996 53.09529 -1.4321933 438120
## 562 48583 12/10/1995 12 10 1995 53.09529 -1.4321933 438120
## 563 48583 12/11/1998 12 11 1998 53.09529 -1.4321933 438120
## 564 48583 13/06/1985 13 6 1985 53.09529 -1.4321933 438120
## 565 48583 14/06/1990 14 6 1990 53.09529 -1.4321933 438120
## 566 48583 15/10/1997 15 10 1997 53.09529 -1.4321933 438120
## 567 48583 16/11/2018 16 11 2018 53.09529 -1.4321933 438120
## 568 48583 17/02/1993 17 2 1993 53.09529 -1.4321933 438120
## 569 48583 17/03/1998 17 3 1998 53.09529 -1.4321933 438120
## 570 48583 17/04/1996 17 4 1996 53.09529 -1.4321933 438120
## 571 48583 17/09/2015 17 9 2015 53.09529 -1.4321933 438120
## 572 48583 18/09/1991 18 9 1991 53.09529 -1.4321933 438120
## 573 48583 19/02/1992 19 2 1992 53.09529 -1.4321933 438120
## 574 48583 19/10/2004 19 10 2004 53.09529 -1.4321933 438120
## 575 48583 19/11/1985 19 11 1985 53.09529 -1.4321933 438120
## 576 48583 20/07/1989 20 7 1989 53.09529 -1.4321933 438120
## 577 48583 20/07/1992 20 7 1992 53.09529 -1.4321933 438120
## 578 48583 21/06/1993 21 6 1993 53.09529 -1.4321933 438120
## 579 48583 21/09/1992 21 9 1992 53.09529 -1.4321933 438120
## 580 48583 22/02/1994 22 2 1994 53.09529 -1.4321933 438120
## 581 48583 23/09/1993 23 9 1993 53.09529 -1.4321933 438120
## 582 48583 24/04/2007 24 4 2007 53.09529 -1.4321933 438120
## 583 48583 24/05/2000 24 5 2000 53.09529 -1.4321933 438120
## 584 48583 25/02/1986 25 2 1986 53.09529 -1.4321933 438120
## 585 48583 25/09/1990 25 9 1990 53.09529 -1.4321933 438120
## 586 48583 25/10/2007 25 10 2007 53.09529 -1.4321933 438120
## 587 48583 27/03/2019 27 3 2019 53.09529 -1.4321933 438120
## 588 48583 27/10/1999 27 10 1999 53.09529 -1.4321933 438120
## 589 48583 29/03/2004 29 3 2004 53.09529 -1.4321933 438120
## 590 48583 29/06/1994 29 6 1994 53.09529 -1.4321933 438120
## 591 48583 30/01/1985 30 1 1985 53.09529 -1.4321933 438120
## 592 48583 30/04/1985 30 4 1985 53.09529 -1.4321933 438120
## 593 48583 30/06/1988 30 6 1988 53.09529 -1.4321933 438120
## 594 48583 30/11/2000 30 11 2000 53.09529 -1.4321933 438120
## 595 48583 30/11/2001 30 11 2001 53.09529 -1.4321933 438120
## 596 48583 31/03/2015 31 3 2015 53.09529 -1.4321933 438120
## 597 48583 31/05/2012 31 5 2012 53.09529 -1.4321933 438120
## 598 48601 01/05/1990 1 5 1990 52.58120 -1.1869470 455189
## 599 48601 01/10/1986 1 10 1986 52.58120 -1.1869470 455189
## 600 48601 03/04/1993 3 4 1993 52.58120 -1.1869470 455189
## 601 48601 04/12/1985 4 12 1985 52.58120 -1.1869470 455189
## 602 48601 06/03/1986 6 3 1986 52.58120 -1.1869470 455189
## 603 48601 07/08/1990 7 8 1990 52.58120 -1.1869470 455189
## 604 48601 07/10/2010 7 10 2010 52.58120 -1.1869470 455189
## 605 48601 08/08/1996 8 8 1996 52.58120 -1.1869470 455189
## 606 48601 08/11/1994 8 11 1994 52.58120 -1.1869470 455189
## 607 48601 09/04/1995 9 4 1995 52.58120 -1.1869470 455189
## 608 48601 10/04/2000 10 4 2000 52.58120 -1.1869470 455189
## 609 48601 10/10/1990 10 10 1990 52.58120 -1.1869470 455189
## 610 48601 10/12/1986 10 12 1986 52.58120 -1.1869470 455189
## 611 48601 11/07/1991 11 7 1991 52.58120 -1.1869470 455189
## 612 48601 12/05/1986 12 5 1986 52.58120 -1.1869470 455189
## 613 48601 12/05/1998 12 5 1998 52.58120 -1.1869470 455189
## 614 48601 12/05/2010 12 5 2010 52.58120 -1.1869470 455189
## 615 48601 13/08/1987 13 8 1987 52.58120 -1.1869470 455189
## 616 48601 13/08/1997 13 8 1997 52.58120 -1.1869470 455189
## 617 48601 13/09/1989 13 9 1989 52.58120 -1.1869470 455189
## 618 48601 14/10/1992 14 10 1992 52.58120 -1.1869470 455189
## 619 48601 15/04/1991 15 4 1991 52.58120 -1.1869470 455189
## 620 48601 15/11/1989 15 11 1989 52.58120 -1.1869470 455189
## 621 48601 16/04/2003 16 4 2003 52.58120 -1.1869470 455189
## 622 48601 17/06/1985 17 6 1985 52.58120 -1.1869470 455189
## 623 48601 17/08/1987 17 8 1987 52.58120 -1.1869470 455189
## 624 48601 17/12/1996 17 12 1996 52.58120 -1.1869470 455189
## 625 48601 18/04/1988 18 4 1988 52.58120 -1.1869470 455189
## 626 48601 18/04/1994 18 4 1994 52.58120 -1.1869470 455189
## 627 48601 19/05/2014 19 5 2014 52.58120 -1.1869470 455189
## 628 48601 19/10/2006 19 10 2006 52.58120 -1.1869470 455189
## 629 48601 19/11/1998 19 11 1998 52.58120 -1.1869470 455189
## 630 48601 20/05/2004 20 5 2004 52.58120 -1.1869470 455189
## 631 48601 20/07/1993 20 7 1993 52.58120 -1.1869470 455189
## 632 48601 21/03/2006 21 3 2006 52.58120 -1.1869470 455189
## 633 48601 22/02/1988 22 2 1988 52.58120 -1.1869470 455189
## 634 48601 22/05/1989 22 5 1989 52.58120 -1.1869470 455189
## 635 48601 22/05/2009 22 5 2009 52.58120 -1.1869470 455189
## 636 48601 22/05/2012 22 5 2012 52.58120 -1.1869470 455189
## 637 48601 22/10/2009 22 10 2009 52.58120 -1.1869470 455189
## 638 48601 22/11/1988 22 11 1988 52.58120 -1.1869470 455189
## 639 48601 23/03/1992 23 3 1992 52.58120 -1.1869470 455189
## 640 48601 23/10/2000 23 10 2000 52.58120 -1.1869470 455189
## 641 48601 24/04/2002 24 4 2002 52.58120 -1.1869470 455189
## 642 48601 24/09/2014 24 9 2014 52.58120 -1.1869470 455189
## 643 48601 25/02/1985 25 2 1985 52.58120 -1.1869470 455189
## 644 48601 25/11/1997 25 11 1997 52.58120 -1.1869470 455189
## 645 48601 26/07/1994 26 7 1994 52.58120 -1.1869470 455189
## 646 48601 26/10/1995 26 10 1995 52.58120 -1.1869470 455189
## 647 48601 26/11/1987 26 11 1987 52.58120 -1.1869470 455189
## 648 48601 27/10/1993 27 10 1993 52.58120 -1.1869470 455189
## 649 48601 27/12/2004 27 12 2004 52.58120 -1.1869470 455189
## 650 48601 28/09/1990 28 9 1990 52.58120 -1.1869470 455189
## 651 48601 28/10/1991 28 10 1991 52.58120 -1.1869470 455189
## 652 48601 29/11/1999 29 11 1999 52.58120 -1.1869470 455189
## 653 48601 29/11/2001 29 11 2001 52.58120 -1.1869470 455189
## 654 48601 30/04/1987 30 4 1987 52.58120 -1.1869470 455189
## 655 48601 30/10/2003 30 10 2003 52.58120 -1.1869470 455189
## 656 48601 30/11/2004 30 11 2004 52.58120 -1.1869470 455189
## 657 49006 01/05/1996 1 5 1996 53.41473 -1.0226726 465057
## 658 49006 02/10/2013 2 10 2013 53.41473 -1.0226726 465057
## 659 49006 03/04/1992 3 4 1992 53.41473 -1.0226726 465057
## 660 49006 05/02/1993 5 2 1993 53.41473 -1.0226726 465057
## 661 49006 05/11/1994 5 11 1994 53.41473 -1.0226726 465057
## 662 49006 06/09/2005 6 9 2005 53.41473 -1.0226726 465057
## 663 49006 07/05/1987 7 5 1987 53.41473 -1.0226726 465057
## 664 49006 08/05/2014 8 5 2014 53.41473 -1.0226726 465057
## 665 49006 09/05/2002 9 5 2002 53.41473 -1.0226726 465057
## 666 49006 09/05/2013 9 5 2013 53.41473 -1.0226726 465057
## 667 49006 10/04/1990 10 4 1990 53.41473 -1.0226726 465057
## 668 49006 10/04/1995 10 4 1995 53.41473 -1.0226726 465057
## 669 49006 10/05/2005 10 5 2005 53.41473 -1.0226726 465057
## 670 49006 10/10/1991 10 10 1991 53.41473 -1.0226726 465057
## 671 49006 10/11/1988 10 11 1988 53.41473 -1.0226726 465057
## 672 49006 12/06/1989 12 6 1989 53.41473 -1.0226726 465057
## 673 49006 13/05/2004 13 5 2004 53.41473 -1.0226726 465057
## 674 49006 14/10/1987 14 10 1987 53.41473 -1.0226726 465057
## 675 49006 15/04/1991 15 4 1991 53.41473 -1.0226726 465057
## 676 49006 15/04/2007 15 4 2007 53.41473 -1.0226726 465057
## 677 49006 15/07/1986 15 7 1986 53.41473 -1.0226726 465057
## 678 49006 15/07/1993 15 7 1993 53.41473 -1.0226726 465057
## 679 49006 15/10/1986 15 10 1986 53.41473 -1.0226726 465057
## 680 49006 16/02/1994 16 2 1994 53.41473 -1.0226726 465057
## 681 49006 16/07/1992 16 7 1992 53.41473 -1.0226726 465057
## 682 49006 16/10/1989 16 10 1989 53.41473 -1.0226726 465057
## 683 49006 16/11/2000 16 11 2000 53.41473 -1.0226726 465057
## 684 49006 17/11/1995 17 11 1995 53.41473 -1.0226726 465057
## 685 49006 17/11/2004 17 11 2004 53.41473 -1.0226726 465057
## 686 49006 18/10/1993 18 10 1993 53.41473 -1.0226726 465057
## 687 49006 19/12/1996 19 12 1996 53.41473 -1.0226726 465057
## 688 49006 20/05/1985 20 5 1985 53.41473 -1.0226726 465057
## 689 49006 20/05/1999 20 5 1999 53.41473 -1.0226726 465057
## 690 49006 21/05/1985 21 5 1985 53.41473 -1.0226726 465057
## 691 49006 21/07/1994 21 7 1994 53.41473 -1.0226726 465057
## 692 49006 22/03/1993 22 3 1993 53.41473 -1.0226726 465057
## 693 49006 23/10/1985 23 10 1985 53.41473 -1.0226726 465057
## 694 49006 24/04/1985 24 4 1985 53.41473 -1.0226726 465057
## 695 49006 24/04/1988 24 4 1988 53.41473 -1.0226726 465057
## 696 49006 24/05/2000 24 5 2000 53.41473 -1.0226726 465057
## 697 49006 24/06/1987 24 6 1987 53.41473 -1.0226726 465057
## 698 49006 24/09/2014 24 9 2014 53.41473 -1.0226726 465057
## 699 49006 24/10/2007 24 10 2007 53.41473 -1.0226726 465057
## 700 49006 26/06/1991 26 6 1991 53.41473 -1.0226726 465057
## 701 49006 26/07/1990 26 7 1990 53.41473 -1.0226726 465057
## 702 49006 26/11/1998 26 11 1998 53.41473 -1.0226726 465057
## 703 49006 28/04/1998 28 4 1998 53.41473 -1.0226726 465057
## 704 49006 28/11/1985 28 11 1985 53.41473 -1.0226726 465057
## 705 49006 29/08/1997 29 8 1997 53.41473 -1.0226726 465057
## 706 49006 30/04/1986 30 4 1986 53.41473 -1.0226726 465057
## 707 49006 30/10/1990 30 10 1990 53.41473 -1.0226726 465057
## 708 49006 30/11/1997 30 11 1997 53.41473 -1.0226726 465057
## 709 49026 02/11/2010 2 11 2010 53.48590 -0.6522800 489525
## 710 49026 03/06/1999 3 6 1999 53.48590 -0.6522800 489525
## 711 49026 03/11/1993 3 11 1993 53.48590 -0.6522800 489525
## 712 49026 04/05/1995 4 5 1995 53.48590 -0.6522800 489525
## 713 49026 05/03/1993 5 3 1993 53.48590 -0.6522800 489525
## 714 49026 05/03/2013 5 3 2013 53.48590 -0.6522800 489525
## 715 49026 05/04/1990 5 4 1990 53.48590 -0.6522800 489525
## 716 49026 05/04/1991 5 4 1991 53.48590 -0.6522800 489525
## 717 49026 05/08/1992 5 8 1992 53.48590 -0.6522800 489525
## 718 49026 05/09/2011 5 9 2011 53.48590 -0.6522800 489525
## 719 49026 06/10/2003 6 10 2003 53.48590 -0.6522800 489525
## 720 49026 07/04/1987 7 4 1987 53.48590 -0.6522800 489525
## 721 49026 07/11/2018 7 11 2018 53.48590 -0.6522800 489525
## 722 49026 08/07/1993 8 7 1993 53.48590 -0.6522800 489525
## 723 49026 08/09/2014 8 9 2014 53.48590 -0.6522800 489525
## 724 49026 08/10/1998 8 10 1998 53.48590 -0.6522800 489525
## 725 49026 08/11/2016 8 11 2016 53.48590 -0.6522800 489525
## 726 49026 09/04/2010 9 4 2010 53.48590 -0.6522800 489525
## 727 49026 11/06/1994 11 6 1994 53.48590 -0.6522800 489525
## 728 49026 12/05/2009 12 5 2009 53.48590 -0.6522800 489525
## 729 49026 13/10/1994 13 10 1994 53.48590 -0.6522800 489525
## 730 49026 14/04/2011 14 4 2011 53.48590 -0.6522800 489525
## 731 49026 14/10/1992 14 10 1992 53.48590 -0.6522800 489525
## 732 49026 14/10/2009 14 10 2009 53.48590 -0.6522800 489525
## 733 49026 14/10/2013 14 10 2013 53.48590 -0.6522800 489525
## 734 49026 15/03/2000 15 3 2000 53.48590 -0.6522800 489525
## 735 49026 15/05/2015 15 5 2015 53.48590 -0.6522800 489525
## 736 49026 15/10/1991 15 10 1991 53.48590 -0.6522800 489525
## 737 49026 15/10/2008 15 10 2008 53.48590 -0.6522800 489525
## 738 49026 16/04/2003 16 4 2003 53.48590 -0.6522800 489525
## 739 49026 16/05/2018 16 5 2018 53.48590 -0.6522800 489525
## 740 49026 16/06/1995 16 6 1995 53.48590 -0.6522800 489525
## 741 49026 16/08/1999 16 8 1999 53.48590 -0.6522800 489525
## 742 49026 17/07/1990 17 7 1990 53.48590 -0.6522800 489525
## 743 49026 18/04/1996 18 4 1996 53.48590 -0.6522800 489525
## 744 49026 18/07/1991 18 7 1991 53.48590 -0.6522800 489525
## 745 49026 20/09/2012 20 9 2012 53.48590 -0.6522800 489525
## 746 49026 20/09/2017 20 9 2017 53.48590 -0.6522800 489525
## 747 49026 20/10/2015 20 10 2015 53.48590 -0.6522800 489525
## 748 49026 21/03/1994 21 3 1994 53.48590 -0.6522800 489525
## 749 49026 21/09/2006 21 9 2006 53.48590 -0.6522800 489525
## 750 49026 21/11/1989 21 11 1989 53.48590 -0.6522800 489525
## 751 49026 22/04/2002 22 4 2002 53.48590 -0.6522800 489525
## 752 49026 22/04/2008 22 4 2008 53.48590 -0.6522800 489525
## 753 49026 23/04/2014 23 4 2014 53.48590 -0.6522800 489525
## 754 49026 23/05/2017 23 5 2017 53.48590 -0.6522800 489525
## 755 49026 23/10/1990 23 10 1990 53.48590 -0.6522800 489525
## 756 49026 24/03/2016 24 3 2016 53.48590 -0.6522800 489525
## 757 49026 24/09/2002 24 9 2002 53.48590 -0.6522800 489525
## 758 49026 24/11/1995 24 11 1995 53.48590 -0.6522800 489525
## 759 49026 25/06/1997 25 6 1997 53.48590 -0.6522800 489525
## 760 49026 25/11/1997 25 11 1997 53.48590 -0.6522800 489525
## 761 49026 26/04/2006 26 4 2006 53.48590 -0.6522800 489525
## 762 49026 27/05/1998 27 5 1998 53.48590 -0.6522800 489525
## 763 49026 28/05/2012 28 5 2012 53.48590 -0.6522800 489525
## 764 49026 28/09/2000 28 9 2000 53.48590 -0.6522800 489525
## 765 49026 30/03/1992 30 3 1992 53.48590 -0.6522800 489525
## 766 49040 01/05/1994 1 5 1994 52.76617 -0.7844495 482114
## 767 49040 01/10/1985 1 10 1985 52.76617 -0.7844495 482114
## 768 49040 01/11/2001 1 11 2001 52.76617 -0.7844495 482114
## 769 49040 02/02/1987 2 2 1987 52.76617 -0.7844495 482114
## 770 49040 03/01/1985 3 1 1985 52.76617 -0.7844495 482114
## 771 49040 03/04/1985 3 4 1985 52.76617 -0.7844495 482114
## 772 49040 04/01/1990 4 1 1990 52.76617 -0.7844495 482114
## 773 49040 04/08/1992 4 8 1992 52.76617 -0.7844495 482114
## 774 49040 04/08/1993 4 8 1993 52.76617 -0.7844495 482114
## 775 49040 05/08/1990 5 8 1990 52.76617 -0.7844495 482114
## 776 49040 05/12/1991 5 12 1991 52.76617 -0.7844495 482114
## 777 49040 07/03/2016 7 3 2016 52.76617 -0.7844495 482114
## 778 49040 07/08/1989 7 8 1989 52.76617 -0.7844495 482114
## 779 49040 07/08/1991 7 8 1991 52.76617 -0.7844495 482114
## 780 49040 07/10/2004 7 10 2004 52.76617 -0.7844495 482114
## 781 49040 09/10/1995 9 10 1995 52.76617 -0.7844495 482114
## 782 49040 09/11/1992 9 11 1992 52.76617 -0.7844495 482114
## 783 49040 11/04/2002 11 4 2002 52.76617 -0.7844495 482114
## 784 49040 12/10/2016 12 10 2016 52.76617 -0.7844495 482114
## 785 49040 13/05/2004 13 5 2004 52.76617 -0.7844495 482114
## 786 49040 14/05/1992 14 5 1992 52.76617 -0.7844495 482114
## 787 49040 14/08/1996 14 8 1996 52.76617 -0.7844495 482114
## 788 49040 14/09/1988 14 9 1988 52.76617 -0.7844495 482114
## 789 49040 15/05/2013 15 5 2013 52.76617 -0.7844495 482114
## 790 49040 16/07/1987 16 7 1987 52.76617 -0.7844495 482114
## 791 49040 16/12/1996 16 12 1996 52.76617 -0.7844495 482114
## 792 49040 17/10/2000 17 10 2000 52.76617 -0.7844495 482114
## 793 49040 17/11/1993 17 11 1993 52.76617 -0.7844495 482114
## 794 49040 18/02/1986 18 2 1986 52.76617 -0.7844495 482114
## 795 49040 18/11/1987 18 11 1987 52.76617 -0.7844495 482114
## 796 49040 20/11/1986 20 11 1986 52.76617 -0.7844495 482114
## 797 49040 20/11/1998 20 11 1998 52.76617 -0.7844495 482114
## 798 49040 21/03/2000 21 3 2000 52.76617 -0.7844495 482114
## 799 49040 21/04/1991 21 4 1991 52.76617 -0.7844495 482114
## 800 49040 21/11/1994 21 11 1994 52.76617 -0.7844495 482114
## 801 49040 24/03/1988 24 3 1988 52.76617 -0.7844495 482114
## 802 49040 24/09/2007 24 9 2007 52.76617 -0.7844495 482114
## 803 49040 24/10/2013 24 10 2013 52.76617 -0.7844495 482114
## 804 49040 25/04/1990 25 4 1990 52.76617 -0.7844495 482114
## 805 49040 25/04/2007 25 4 2007 52.76617 -0.7844495 482114
## 806 49040 25/09/2002 25 9 2002 52.76617 -0.7844495 482114
## 807 49040 26/04/1995 26 4 1995 52.76617 -0.7844495 482114
## 808 49040 27/07/1994 27 7 1994 52.76617 -0.7844495 482114
## 809 49040 27/10/1999 27 10 1999 52.76617 -0.7844495 482114
## 810 49040 27/11/1997 27 11 1997 52.76617 -0.7844495 482114
## 811 49040 28/04/1993 28 4 1993 52.76617 -0.7844495 482114
## 812 49040 29/08/1997 29 8 1997 52.76617 -0.7844495 482114
## 813 49040 30/06/1986 30 6 1986 52.76617 -0.7844495 482114
## 814 49040 30/08/1989 30 8 1989 52.76617 -0.7844495 482114
## 815 49040 30/10/1990 30 10 1990 52.76617 -0.7844495 482114
## 816 49040 31/03/1998 31 3 1998 52.76617 -0.7844495 482114
## 817 49171 03/06/1997 3 6 1997 52.95100 -1.8437111 410598
## 818 49171 05/05/1993 5 5 1993 52.95100 -1.8437111 410598
## 819 49171 05/10/2018 5 10 2018 52.95100 -1.8437111 410598
## 820 49171 05/11/2008 5 11 2008 52.95100 -1.8437111 410598
## 821 49171 06/11/1991 6 11 1991 52.95100 -1.8437111 410598
## 822 49171 06/11/2014 6 11 2014 52.95100 -1.8437111 410598
## 823 49171 07/04/2000 7 4 2000 52.95100 -1.8437111 410598
## 824 49171 07/09/2006 7 9 2006 52.95100 -1.8437111 410598
## 825 49171 08/06/1992 8 6 1992 52.95100 -1.8437111 410598
## 826 49171 08/11/2017 8 11 2017 52.95100 -1.8437111 410598
## 827 49171 09/04/2009 9 4 2009 52.95100 -1.8437111 410598
## 828 49171 09/10/1998 9 10 1998 52.95100 -1.8437111 410598
## 829 49171 10/12/1996 10 12 1996 52.95100 -1.8437111 410598
## 830 49171 11/04/2017 11 4 2017 52.95100 -1.8437111 410598
## 831 49171 12/10/2010 12 10 2010 52.95100 -1.8437111 410598
## 832 49171 14/03/1995 14 3 1995 52.95100 -1.8437111 410598
## 833 49171 14/09/1994 14 9 1994 52.95100 -1.8437111 410598
## 834 49171 14/12/2001 14 12 2001 52.95100 -1.8437111 410598
## 835 49171 15/04/1991 15 4 1991 52.95100 -1.8437111 410598
## 836 49171 15/08/2011 15 8 2011 52.95100 -1.8437111 410598
## 837 49171 16/04/2003 16 4 2003 52.95100 -1.8437111 410598
## 838 49171 16/05/2018 16 5 2018 52.95100 -1.8437111 410598
## 839 49171 17/05/1994 17 5 1994 52.95100 -1.8437111 410598
## 840 49171 19/04/2010 19 4 2010 52.95100 -1.8437111 410598
## 841 49171 19/04/2016 19 4 2016 52.95100 -1.8437111 410598
## 842 49171 19/09/2003 19 9 2003 52.95100 -1.8437111 410598
## 843 49171 19/09/2013 19 9 2013 52.95100 -1.8437111 410598
## 844 49171 19/10/2009 19 10 2009 52.95100 -1.8437111 410598
## 845 49171 19/11/2012 19 11 2012 52.95100 -1.8437111 410598
## 846 49171 20/03/2012 20 3 2012 52.95100 -1.8437111 410598
## 847 49171 20/04/2015 20 4 2015 52.95100 -1.8437111 410598
## 848 49171 20/05/1998 20 5 1998 52.95100 -1.8437111 410598
## 849 49171 20/05/2014 20 5 2014 52.95100 -1.8437111 410598
## 850 49171 20/06/1990 20 6 1990 52.95100 -1.8437111 410598
## 851 49171 20/09/2011 20 9 2011 52.95100 -1.8437111 410598
## 852 49171 21/03/2013 21 3 2013 52.95100 -1.8437111 410598
## 853 49171 22/03/1990 22 3 1990 52.95100 -1.8437111 410598
## 854 49171 22/03/2011 22 3 2011 52.95100 -1.8437111 410598
## 855 49171 23/09/2015 23 9 2015 52.95100 -1.8437111 410598
## 856 49171 23/12/1992 23 12 1992 52.95100 -1.8437111 410598
## 857 49171 24/10/2000 24 10 2000 52.95100 -1.8437111 410598
## 858 49171 25/01/1993 25 1 1993 52.95100 -1.8437111 410598
## 859 49171 25/06/2002 25 6 2002 52.95100 -1.8437111 410598
## 860 49171 25/09/1995 25 9 1995 52.95100 -1.8437111 410598
## 861 49171 25/10/2016 25 10 2016 52.95100 -1.8437111 410598
## 862 49171 25/11/1993 25 11 1993 52.95100 -1.8437111 410598
## 863 49171 26/04/2006 26 4 2006 52.95100 -1.8437111 410598
## 864 49171 26/05/1999 26 5 1999 52.95100 -1.8437111 410598
## 865 49171 26/09/1990 26 9 1990 52.95100 -1.8437111 410598
## 866 49171 26/09/2007 26 9 2007 52.95100 -1.8437111 410598
## 867 49171 28/03/1996 28 3 1996 52.95100 -1.8437111 410598
## 868 49171 28/05/2008 28 5 2008 52.95100 -1.8437111 410598
## 869 49171 28/10/1997 28 10 1997 52.95100 -1.8437111 410598
## 870 49171 29/08/2012 29 8 2012 52.95100 -1.8437111 410598
## 871 49171 31/08/1993 31 8 1993 52.95100 -1.8437111 410598
## 872 49685 01/09/1999 1 9 1999 53.07124 -1.3414209 444223
## 873 49685 01/10/1987 1 10 1987 53.07124 -1.3414209 444223
## 874 49685 01/10/1992 1 10 1992 53.07124 -1.3414209 444223
## 875 49685 03/08/1989 3 8 1989 53.07124 -1.3414209 444223
## 876 49685 04/06/1986 4 6 1986 53.07124 -1.3414209 444223
## 877 49685 04/12/2001 4 12 2001 53.07124 -1.3414209 444223
## 878 49685 05/09/1997 5 9 1997 53.07124 -1.3414209 444223
## 879 49685 05/10/1995 5 10 1995 53.07124 -1.3414209 444223
## 880 49685 05/10/2015 5 10 2015 53.07124 -1.3414209 444223
## 881 49685 06/08/1985 6 8 1985 53.07124 -1.3414209 444223
## 882 49685 07/02/1994 7 2 1994 53.07124 -1.3414209 444223
## 883 49685 07/02/1997 7 2 1997 53.07124 -1.3414209 444223
## 884 49685 07/06/2000 7 6 2000 53.07124 -1.3414209 444223
## 885 49685 09/03/1992 9 3 1992 53.07124 -1.3414209 444223
## 886 49685 09/05/1996 9 5 1996 53.07124 -1.3414209 444223
## 887 49685 09/07/1997 9 7 1997 53.07124 -1.3414209 444223
## 888 49685 09/09/1986 9 9 1986 53.07124 -1.3414209 444223
## 889 49685 10/03/1993 10 3 1993 53.07124 -1.3414209 444223
## 890 49685 10/04/2000 10 4 2000 53.07124 -1.3414209 444223
## 891 49685 10/07/1990 10 7 1990 53.07124 -1.3414209 444223
## 892 49685 11/05/2000 11 5 2000 53.07124 -1.3414209 444223
## 893 49685 11/08/2000 11 8 2000 53.07124 -1.3414209 444223
## 894 49685 11/11/2009 11 11 2009 53.07124 -1.3414209 444223
## 895 49685 11/12/1996 11 12 1996 53.07124 -1.3414209 444223
## 896 49685 12/04/2006 12 4 2006 53.07124 -1.3414209 444223
## 897 49685 12/07/2000 12 7 2000 53.07124 -1.3414209 444223
## 898 49685 12/09/2000 12 9 2000 53.07124 -1.3414209 444223
## 899 49685 13/01/1997 13 1 1997 53.07124 -1.3414209 444223
## 900 49685 14/04/2004 14 4 2004 53.07124 -1.3414209 444223
## 901 49685 14/05/2015 14 5 2015 53.07124 -1.3414209 444223
## 902 49685 14/06/1999 14 6 1999 53.07124 -1.3414209 444223
## 903 49685 14/11/1997 14 11 1997 53.07124 -1.3414209 444223
## 904 49685 15/09/1988 15 9 1988 53.07124 -1.3414209 444223
## 905 49685 15/10/1998 15 10 1998 53.07124 -1.3414209 444223
## 906 49685 16/02/1988 16 2 1988 53.07124 -1.3414209 444223
## 907 49685 16/07/1987 16 7 1987 53.07124 -1.3414209 444223
## 908 49685 17/02/1987 17 2 1987 53.07124 -1.3414209 444223
## 909 49685 17/06/1994 17 6 1994 53.07124 -1.3414209 444223
## 910 49685 17/10/1990 17 10 1990 53.07124 -1.3414209 444223
## 911 49685 18/01/2001 18 1 2001 53.07124 -1.3414209 444223
## 912 49685 18/10/2000 18 10 2000 53.07124 -1.3414209 444223
## 913 49685 19/03/1997 19 3 1997 53.07124 -1.3414209 444223
## 914 49685 20/03/1995 20 3 1995 53.07124 -1.3414209 444223
## 915 49685 20/10/2010 20 10 2010 53.07124 -1.3414209 444223
## 916 49685 21/02/1989 21 2 1989 53.07124 -1.3414209 444223
## 917 49685 21/12/1994 21 12 1994 53.07124 -1.3414209 444223
## 918 49685 23/04/1997 23 4 1997 53.07124 -1.3414209 444223
## 919 49685 23/04/2009 23 4 2009 53.07124 -1.3414209 444223
## 920 49685 24/04/2001 24 4 2001 53.07124 -1.3414209 444223
## 921 49685 24/05/2001 24 5 2001 53.07124 -1.3414209 444223
## 922 49685 24/07/1992 24 7 1992 53.07124 -1.3414209 444223
## 923 49685 25/09/2004 25 9 2004 53.07124 -1.3414209 444223
## 924 49685 26/01/2000 26 1 2000 53.07124 -1.3414209 444223
## 925 49685 26/02/1985 26 2 1985 53.07124 -1.3414209 444223
## 926 49685 27/01/1998 27 1 1998 53.07124 -1.3414209 444223
## 927 49685 27/06/1989 27 6 1989 53.07124 -1.3414209 444223
## 928 49685 27/09/1993 27 9 1993 53.07124 -1.3414209 444223
## 929 49685 28/03/1990 28 3 1990 53.07124 -1.3414209 444223
## 930 49685 28/03/1991 28 3 1991 53.07124 -1.3414209 444223
## 931 49685 28/05/1998 28 5 1998 53.07124 -1.3414209 444223
## 932 49685 28/06/1993 28 6 1993 53.07124 -1.3414209 444223
## 933 49685 28/08/2001 28 8 2001 53.07124 -1.3414209 444223
## 934 49685 29/05/2002 29 5 2002 53.07124 -1.3414209 444223
## 935 49685 29/10/2003 29 10 2003 53.07124 -1.3414209 444223
## 936 49685 30/05/2003 30 5 2003 53.07124 -1.3414209 444223
## 937 49685 30/09/1991 30 9 1991 53.07124 -1.3414209 444223
## 938 49685 30/10/2006 30 10 2006 53.07124 -1.3414209 444223
## 939 49685 30/11/2000 30 11 2000 53.07124 -1.3414209 444223
## 940 49685 31/05/2010 31 5 2010 53.07124 -1.3414209 444223
## 941 49685 31/10/1996 31 10 1996 53.07124 -1.3414209 444223
## 942 49781 01/05/2007 1 5 2007 53.08431 -1.3238433 445387
## 943 49781 01/10/1987 1 10 1987 53.08431 -1.3238433 445387
## 944 49781 01/10/1992 1 10 1992 53.08431 -1.3238433 445387
## 945 49781 02/04/1990 2 4 1990 53.08431 -1.3238433 445387
## 946 49781 03/08/1989 3 8 1989 53.08431 -1.3238433 445387
## 947 49781 03/12/1999 3 12 1999 53.08431 -1.3238433 445387
## 948 49781 04/06/1986 4 6 1986 53.08431 -1.3238433 445387
## 949 49781 05/09/1997 5 9 1997 53.08431 -1.3238433 445387
## 950 49781 05/10/2015 5 10 2015 53.08431 -1.3238433 445387
## 951 49781 06/08/1985 6 8 1985 53.08431 -1.3238433 445387
## 952 49781 07/02/1994 7 2 1994 53.08431 -1.3238433 445387
## 953 49781 07/02/1997 7 2 1997 53.08431 -1.3238433 445387
## 954 49781 07/03/2000 7 3 2000 53.08431 -1.3238433 445387
## 955 49781 07/06/2000 7 6 2000 53.08431 -1.3238433 445387
## 956 49781 07/09/1999 7 9 1999 53.08431 -1.3238433 445387
## 957 49781 08/08/2000 8 8 2000 53.08431 -1.3238433 445387
## 958 49781 09/03/1992 9 3 1992 53.08431 -1.3238433 445387
## 959 49781 09/05/1996 9 5 1996 53.08431 -1.3238433 445387
## 960 49781 09/07/1997 9 7 1997 53.08431 -1.3238433 445387
## 961 49781 09/09/1986 9 9 1986 53.08431 -1.3238433 445387
## 962 49781 10/03/1993 10 3 1993 53.08431 -1.3238433 445387
## 963 49781 10/04/2000 10 4 2000 53.08431 -1.3238433 445387
## 964 49781 10/07/1990 10 7 1990 53.08431 -1.3238433 445387
## 965 49781 11/05/2000 11 5 2000 53.08431 -1.3238433 445387
## 966 49781 11/10/1995 11 10 1995 53.08431 -1.3238433 445387
## 967 49781 11/11/2009 11 11 2009 53.08431 -1.3238433 445387
## 968 49781 11/12/1996 11 12 1996 53.08431 -1.3238433 445387
## 969 49781 12/07/2000 12 7 2000 53.08431 -1.3238433 445387
## 970 49781 12/09/2000 12 9 2000 53.08431 -1.3238433 445387
## 971 49781 13/01/1997 13 1 1997 53.08431 -1.3238433 445387
## 972 49781 14/04/2004 14 4 2004 53.08431 -1.3238433 445387
## 973 49781 14/11/1997 14 11 1997 53.08431 -1.3238433 445387
## 974 49781 15/09/1988 15 9 1988 53.08431 -1.3238433 445387
## 975 49781 15/10/1998 15 10 1998 53.08431 -1.3238433 445387
## 976 49781 16/02/1988 16 2 1988 53.08431 -1.3238433 445387
## 977 49781 16/07/1987 16 7 1987 53.08431 -1.3238433 445387
## 978 49781 17/02/1987 17 2 1987 53.08431 -1.3238433 445387
## 979 49781 17/06/1994 17 6 1994 53.08431 -1.3238433 445387
## 980 49781 17/10/1990 17 10 1990 53.08431 -1.3238433 445387
## 981 49781 18/01/2001 18 1 2001 53.08431 -1.3238433 445387
## 982 49781 18/10/2000 18 10 2000 53.08431 -1.3238433 445387
## 983 49781 19/03/1997 19 3 1997 53.08431 -1.3238433 445387
## 984 49781 20/03/1995 20 3 1995 53.08431 -1.3238433 445387
## 985 49781 20/10/2010 20 10 2010 53.08431 -1.3238433 445387
## 986 49781 21/02/1989 21 2 1989 53.08431 -1.3238433 445387
## 987 49781 21/12/1994 21 12 1994 53.08431 -1.3238433 445387
## 988 49781 21/12/2001 21 12 2001 53.08431 -1.3238433 445387
## 989 49781 23/04/1997 23 4 1997 53.08431 -1.3238433 445387
## 990 49781 23/04/2009 23 4 2009 53.08431 -1.3238433 445387
## 991 49781 24/04/2001 24 4 2001 53.08431 -1.3238433 445387
## 992 49781 24/05/2001 24 5 2001 53.08431 -1.3238433 445387
## 993 49781 24/07/1992 24 7 1992 53.08431 -1.3238433 445387
## 994 49781 25/09/2004 25 9 2004 53.08431 -1.3238433 445387
## 995 49781 26/01/2000 26 1 2000 53.08431 -1.3238433 445387
## 996 49781 26/02/1985 26 2 1985 53.08431 -1.3238433 445387
## 997 49781 26/10/2007 26 10 2007 53.08431 -1.3238433 445387
## 998 49781 27/01/1998 27 1 1998 53.08431 -1.3238433 445387
## 999 49781 27/09/1993 27 9 1993 53.08431 -1.3238433 445387
## 1000 49781 28/03/1991 28 3 1991 53.08431 -1.3238433 445387
## 1001 49781 28/05/1998 28 5 1998 53.08431 -1.3238433 445387
## 1002 49781 28/06/1993 28 6 1993 53.08431 -1.3238433 445387
## 1003 49781 28/08/2001 28 8 2001 53.08431 -1.3238433 445387
## 1004 49781 29/05/2002 29 5 2002 53.08431 -1.3238433 445387
## 1005 49781 29/10/2003 29 10 2003 53.08431 -1.3238433 445387
## 1006 49781 30/09/1991 30 9 1991 53.08431 -1.3238433 445387
## 1007 49781 30/11/2000 30 11 2000 53.08431 -1.3238433 445387
## 1008 49781 31/03/2015 31 3 2015 53.08431 -1.3238433 445387
## 1009 49781 31/05/2010 31 5 2010 53.08431 -1.3238433 445387
## 1010 49781 31/10/1996 31 10 1996 53.08431 -1.3238433 445387
## 1011 49881 01/07/1985 1 7 1985 52.46394 -1.6805148 421803
## 1012 49881 01/11/1989 1 11 1989 52.46394 -1.6805148 421803
## 1013 49881 03/06/1996 3 6 1996 52.46394 -1.6805148 421803
## 1014 49881 03/11/2004 3 11 2004 52.46394 -1.6805148 421803
## 1015 49881 06/07/1992 6 7 1992 52.46394 -1.6805148 421803
## 1016 49881 06/09/1983 6 9 1983 52.46394 -1.6805148 421803
## 1017 49881 07/06/1983 7 6 1983 52.46394 -1.6805148 421803
## 1018 49881 07/08/1990 7 8 1990 52.46394 -1.6805148 421803
## 1019 49881 07/09/1987 7 9 1987 52.46394 -1.6805148 421803
## 1020 49881 07/11/1994 7 11 1994 52.46394 -1.6805148 421803
## 1021 49881 08/03/1984 8 3 1984 52.46394 -1.6805148 421803
## 1022 49881 08/09/1982 8 9 1982 52.46394 -1.6805148 421803
## 1023 49881 08/11/1983 8 11 1983 52.46394 -1.6805148 421803
## 1024 49881 09/05/1995 9 5 1995 52.46394 -1.6805148 421803
## 1025 49881 11/12/2001 11 12 2001 52.46394 -1.6805148 421803
## 1026 49881 12/03/2003 12 3 2003 52.46394 -1.6805148 421803
## 1027 49881 14/03/1994 14 3 1994 52.46394 -1.6805148 421803
## 1028 49881 15/02/1988 15 2 1988 52.46394 -1.6805148 421803
## 1029 49881 15/03/2007 15 3 2007 52.46394 -1.6805148 421803
## 1030 49881 16/04/1991 16 4 1991 52.46394 -1.6805148 421803
## 1031 49881 16/05/1990 16 5 1990 52.46394 -1.6805148 421803
## 1032 49881 16/06/1999 16 6 1999 52.46394 -1.6805148 421803
## 1033 49881 17/02/1983 17 2 1983 52.46394 -1.6805148 421803
## 1034 49881 17/03/1987 17 3 1987 52.46394 -1.6805148 421803
## 1035 49881 17/05/1993 17 5 1993 52.46394 -1.6805148 421803
## 1036 49881 17/06/1997 17 6 1997 52.46394 -1.6805148 421803
## 1037 49881 18/02/1985 18 2 1985 52.46394 -1.6805148 421803
## 1038 49881 18/07/1988 18 7 1988 52.46394 -1.6805148 421803
## 1039 49881 18/09/2000 18 9 2000 52.46394 -1.6805148 421803
## 1040 49881 18/10/1993 18 10 1993 52.46394 -1.6805148 421803
## 1041 49881 18/11/1985 18 11 1985 52.46394 -1.6805148 421803
## 1042 49881 20/03/2000 20 3 2000 52.46394 -1.6805148 421803
## 1043 49881 20/06/1994 20 6 1994 52.46394 -1.6805148 421803
## 1044 49881 20/10/1982 20 10 1982 52.46394 -1.6805148 421803
## 1045 49881 21/01/1998 21 1 1998 52.46394 -1.6805148 421803
## 1046 49881 21/09/2006 21 9 2006 52.46394 -1.6805148 421803
## 1047 49881 21/10/1991 21 10 1991 52.46394 -1.6805148 421803
## 1048 49881 21/11/1988 21 11 1988 52.46394 -1.6805148 421803
## 1049 49881 21/11/1990 21 11 1990 52.46394 -1.6805148 421803
## 1050 49881 22/10/1992 22 10 1992 52.46394 -1.6805148 421803
## 1051 49881 22/11/2007 22 11 2007 52.46394 -1.6805148 421803
## 1052 49881 23/03/1992 23 3 1992 52.46394 -1.6805148 421803
## 1053 49881 23/09/1996 23 9 1996 52.46394 -1.6805148 421803
## 1054 49881 24/01/1983 24 1 1983 52.46394 -1.6805148 421803
## 1055 49881 24/02/1993 24 2 1993 52.46394 -1.6805148 421803
## 1056 49881 24/03/2006 24 3 2006 52.46394 -1.6805148 421803
## 1057 49881 25/05/1989 25 5 1989 52.46394 -1.6805148 421803
## 1058 49881 27/05/1998 27 5 1998 52.46394 -1.6805148 421803
## 1059 49881 28/04/1986 28 4 1986 52.46394 -1.6805148 421803
## 1060 49881 28/05/2004 28 5 2004 52.46394 -1.6805148 421803
## 1061 49881 29/09/1986 29 9 1986 52.46394 -1.6805148 421803
## 1062 49881 30/10/1995 30 10 1995 52.46394 -1.6805148 421803
## 1063 49881 30/11/1998 30 11 1998 52.46394 -1.6805148 421803
## 1064 50020 02/05/2003 2 5 2003 52.68348 -1.2286142 452244
## 1065 50020 02/07/1991 2 7 1991 52.68348 -1.2286142 452244
## 1066 50020 02/09/2015 2 9 2015 52.68348 -1.2286142 452244
## 1067 50020 02/10/2013 2 10 2013 52.68348 -1.2286142 452244
## 1068 50020 02/11/2004 2 11 2004 52.68348 -1.2286142 452244
## 1069 50020 03/04/1991 3 4 1991 52.68348 -1.2286142 452244
## 1070 50020 03/04/2017 3 4 2017 52.68348 -1.2286142 452244
## 1071 50020 04/04/1997 4 4 1997 52.68348 -1.2286142 452244
## 1072 50020 04/04/2005 4 4 2005 52.68348 -1.2286142 452244
## 1073 50020 05/10/1987 5 10 1987 52.68348 -1.2286142 452244
## 1074 50020 05/10/1996 5 10 1996 52.68348 -1.2286142 452244
## 1075 50020 05/12/1988 5 12 1988 52.68348 -1.2286142 452244
## 1076 50020 06/11/2017 6 11 2017 52.68348 -1.2286142 452244
## 1077 50020 07/08/2007 7 8 2007 52.68348 -1.2286142 452244
## 1078 50020 07/10/1991 7 10 1991 52.68348 -1.2286142 452244
## 1079 50020 07/10/2010 7 10 2010 52.68348 -1.2286142 452244
## 1080 50020 08/02/1987 8 2 1987 52.68348 -1.2286142 452244
## 1081 50020 08/03/1995 8 3 1995 52.68348 -1.2286142 452244
## 1082 50020 08/07/1992 8 7 1992 52.68348 -1.2286142 452244
## 1083 50020 08/08/1995 8 8 1995 52.68348 -1.2286142 452244
## 1084 50020 08/11/1999 8 11 1999 52.68348 -1.2286142 452244
## 1085 50020 09/03/1992 9 3 1992 52.68348 -1.2286142 452244
## 1086 50020 09/05/2013 9 5 2013 52.68348 -1.2286142 452244
## 1087 50020 09/05/2018 9 5 2018 52.68348 -1.2286142 452244
## 1088 50020 09/12/1985 9 12 1985 52.68348 -1.2286142 452244
## 1089 50020 10/04/2000 10 4 2000 52.68348 -1.2286142 452244
## 1090 50020 10/10/2016 10 10 2016 52.68348 -1.2286142 452244
## 1091 50020 11/03/1993 11 3 1993 52.68348 -1.2286142 452244
## 1092 50020 11/07/1986 11 7 1986 52.68348 -1.2286142 452244
## 1093 50020 11/09/2018 11 9 2018 52.68348 -1.2286142 452244
## 1094 50020 12/06/1996 12 6 1996 52.68348 -1.2286142 452244
## 1095 50020 12/07/2006 12 7 2006 52.68348 -1.2286142 452244
## 1096 50020 12/08/2008 12 8 2008 52.68348 -1.2286142 452244
## 1097 50020 12/12/1986 12 12 1986 52.68348 -1.2286142 452244
## 1098 50020 13/03/1986 13 3 1986 52.68348 -1.2286142 452244
## 1099 50020 13/04/2016 13 4 2016 52.68348 -1.2286142 452244
## 1100 50020 13/07/1999 13 7 1999 52.68348 -1.2286142 452244
## 1101 50020 13/11/2008 13 11 2008 52.68348 -1.2286142 452244
## 1102 50020 15/04/1985 15 4 1985 52.68348 -1.2286142 452244
## 1103 50020 15/09/2011 15 9 2011 52.68348 -1.2286142 452244
## 1104 50020 17/04/1990 17 4 1990 52.68348 -1.2286142 452244
## 1105 50020 17/05/1988 17 5 1988 52.68348 -1.2286142 452244
## 1106 50020 17/05/2011 17 5 2011 52.68348 -1.2286142 452244
## 1107 50020 17/08/2001 17 8 2001 52.68348 -1.2286142 452244
## 1108 50020 17/09/2012 17 9 2012 52.68348 -1.2286142 452244
## 1109 50020 18/07/1985 18 7 1985 52.68348 -1.2286142 452244
## 1110 50020 18/07/1990 18 7 1990 52.68348 -1.2286142 452244
## 1111 50020 18/08/2009 18 8 2009 52.68348 -1.2286142 452244
## 1112 50020 19/08/2003 19 8 2003 52.68348 -1.2286142 452244
## 1113 50020 19/08/2005 19 8 2005 52.68348 -1.2286142 452244
## 1114 50020 19/10/1994 19 10 1994 52.68348 -1.2286142 452244
## 1115 50020 19/10/2009 19 10 2009 52.68348 -1.2286142 452244
## 1116 50020 19/12/1993 19 12 1993 52.68348 -1.2286142 452244
## 1117 50020 20/04/1999 20 4 1999 52.68348 -1.2286142 452244
## 1118 50020 20/07/1989 20 7 1989 52.68348 -1.2286142 452244
## 1119 50020 20/10/2000 20 10 2000 52.68348 -1.2286142 452244
## 1120 50020 20/11/2001 20 11 2001 52.68348 -1.2286142 452244
## 1121 50020 21/03/2014 21 3 2014 52.68348 -1.2286142 452244
## 1122 50020 21/10/2002 21 10 2002 52.68348 -1.2286142 452244
## 1123 50020 22/02/1994 22 2 1994 52.68348 -1.2286142 452244
## 1124 50020 22/04/1998 22 4 1998 52.68348 -1.2286142 452244
## 1125 50020 22/06/1987 22 6 1987 52.68348 -1.2286142 452244
## 1126 50020 22/07/2004 22 7 2004 52.68348 -1.2286142 452244
## 1127 50020 22/07/2011 22 7 2011 52.68348 -1.2286142 452244
## 1128 50020 22/09/2003 22 9 2003 52.68348 -1.2286142 452244
## 1129 50020 23/05/2012 23 5 2012 52.68348 -1.2286142 452244
## 1130 50020 23/10/2007 23 10 2007 52.68348 -1.2286142 452244
## 1131 50020 24/04/2009 24 4 2009 52.68348 -1.2286142 452244
## 1132 50020 24/10/2014 24 10 2014 52.68348 -1.2286142 452244
## 1133 50020 24/11/1998 24 11 1998 52.68348 -1.2286142 452244
## 1134 50020 25/05/2007 25 5 2007 52.68348 -1.2286142 452244
## 1135 50020 25/10/2005 25 10 2005 52.68348 -1.2286142 452244
## 1136 50020 26/03/2004 26 3 2004 52.68348 -1.2286142 452244
## 1137 50020 26/10/1995 26 10 1995 52.68348 -1.2286142 452244
## 1138 50020 27/08/1998 27 8 1998 52.68348 -1.2286142 452244
## 1139 50020 28/05/2008 28 5 2008 52.68348 -1.2286142 452244
## 1140 50020 28/06/1993 28 6 1993 52.68348 -1.2286142 452244
## 1141 50020 28/08/1997 28 8 1997 52.68348 -1.2286142 452244
## 1142 50020 28/08/2002 28 8 2002 52.68348 -1.2286142 452244
## 1143 50020 29/04/1996 29 4 1996 52.68348 -1.2286142 452244
## 1144 50020 29/04/2010 29 4 2010 52.68348 -1.2286142 452244
## 1145 50020 29/04/2015 29 4 2015 52.68348 -1.2286142 452244
## 1146 50020 29/05/2002 29 5 2002 52.68348 -1.2286142 452244
## 1147 50020 29/09/1992 29 9 1992 52.68348 -1.2286142 452244
## 1148 50020 29/09/2006 29 9 2006 52.68348 -1.2286142 452244
## 1149 50020 29/10/1990 29 10 1990 52.68348 -1.2286142 452244
## 1150 50020 30/06/1997 30 6 1997 52.68348 -1.2286142 452244
## 1151 50020 31/05/2006 31 5 2006 52.68348 -1.2286142 452244
## 1152 50020 31/07/2000 31 7 2000 52.68348 -1.2286142 452244
## 1153 50031 01/05/2013 1 5 2013 52.83075 -1.9289073 404887
## 1154 50031 01/06/1992 1 6 1992 52.83075 -1.9289073 404887
## 1155 50031 01/09/2016 1 9 2016 52.83075 -1.9289073 404887
## 1156 50031 01/11/2017 1 11 2017 52.83075 -1.9289073 404887
## 1157 50031 02/10/1985 2 10 1985 52.83075 -1.9289073 404887
## 1158 50031 03/05/2018 3 5 2018 52.83075 -1.9289073 404887
## 1159 50031 03/09/2013 3 9 2013 52.83075 -1.9289073 404887
## 1160 50031 04/09/2002 4 9 2002 52.83075 -1.9289073 404887
## 1161 50031 05/05/2010 5 5 2010 52.83075 -1.9289073 404887
## 1162 50031 05/07/1988 5 7 1988 52.83075 -1.9289073 404887
## 1163 50031 05/10/2009 5 10 2009 52.83075 -1.9289073 404887
## 1164 50031 05/11/1990 5 11 1990 52.83075 -1.9289073 404887
## 1165 50031 06/04/1994 6 4 1994 52.83075 -1.9289073 404887
## 1166 50031 06/10/1986 6 10 1986 52.83075 -1.9289073 404887
## 1167 50031 06/10/2000 6 10 2000 52.83075 -1.9289073 404887
## 1168 50031 07/04/2003 7 4 2003 52.83075 -1.9289073 404887
## 1169 50031 07/05/2014 7 5 2014 52.83075 -1.9289073 404887
## 1170 50031 08/10/1987 8 10 1987 52.83075 -1.9289073 404887
## 1171 50031 08/11/1993 8 11 1993 52.83075 -1.9289073 404887
## 1172 50031 09/01/1995 9 1 1995 52.83075 -1.9289073 404887
## 1173 50031 09/04/2008 9 4 2008 52.83075 -1.9289073 404887
## 1174 50031 09/10/2001 9 10 2001 52.83075 -1.9289073 404887
## 1175 50031 09/10/2018 9 10 2018 52.83075 -1.9289073 404887
## 1176 50031 10/04/2015 10 4 2015 52.83075 -1.9289073 404887
## 1177 50031 10/10/1988 10 10 1988 52.83075 -1.9289073 404887
## 1178 50031 10/10/1997 10 10 1997 52.83075 -1.9289073 404887
## 1179 50031 10/11/1995 10 11 1995 52.83075 -1.9289073 404887
## 1180 50031 11/03/1985 11 3 1985 52.83075 -1.9289073 404887
## 1181 50031 11/04/2000 11 4 2000 52.83075 -1.9289073 404887
## 1182 50031 11/04/2017 11 4 2017 52.83075 -1.9289073 404887
## 1183 50031 11/05/2007 11 5 2007 52.83075 -1.9289073 404887
## 1184 50031 13/08/2013 13 8 2013 52.83075 -1.9289073 404887
## 1185 50031 13/10/2011 13 10 2011 52.83075 -1.9289073 404887
## 1186 50031 13/12/1988 13 12 1988 52.83075 -1.9289073 404887
## 1187 50031 14/04/2016 14 4 2016 52.83075 -1.9289073 404887
## 1188 50031 14/07/1993 14 7 1993 52.83075 -1.9289073 404887
## 1189 50031 15/03/2005 15 3 2005 52.83075 -1.9289073 404887
## 1190 50031 15/04/1985 15 4 1985 52.83075 -1.9289073 404887
## 1191 50031 15/06/1988 15 6 1988 52.83075 -1.9289073 404887
## 1192 50031 16/02/1992 16 2 1992 52.83075 -1.9289073 404887
## 1193 50031 17/07/1985 17 7 1985 52.83075 -1.9289073 404887
## 1194 50031 17/07/1989 17 7 1989 52.83075 -1.9289073 404887
## 1195 50031 17/11/1998 17 11 1998 52.83075 -1.9289073 404887
## 1196 50031 18/04/1996 18 4 1996 52.83075 -1.9289073 404887
## 1197 50031 18/04/2011 18 4 2011 52.83075 -1.9289073 404887
## 1198 50031 18/05/1990 18 5 1990 52.83075 -1.9289073 404887
## 1199 50031 18/09/2008 18 9 2008 52.83075 -1.9289073 404887
## 1200 50031 18/12/1985 18 12 1985 52.83075 -1.9289073 404887
## 1201 50031 19/07/1990 19 7 1990 52.83075 -1.9289073 404887
## 1202 50031 20/02/1991 20 2 1991 52.83075 -1.9289073 404887
## 1203 50031 20/03/2012 20 3 2012 52.83075 -1.9289073 404887
## 1204 50031 20/10/1987 20 10 1987 52.83075 -1.9289073 404887
## 1205 50031 21/01/1988 21 1 1988 52.83075 -1.9289073 404887
## 1206 50031 21/03/2006 21 3 2006 52.83075 -1.9289073 404887
## 1207 50031 21/04/1998 21 4 1998 52.83075 -1.9289073 404887
## 1208 50031 21/05/2009 21 5 2009 52.83075 -1.9289073 404887
## 1209 50031 21/09/2005 21 9 2005 52.83075 -1.9289073 404887
## 1210 50031 22/04/1986 22 4 1986 52.83075 -1.9289073 404887
## 1211 50031 22/05/1995 22 5 1995 52.83075 -1.9289073 404887
## 1212 50031 22/08/2012 22 8 2012 52.83075 -1.9289073 404887
## 1213 50031 23/01/1987 23 1 1987 52.83075 -1.9289073 404887
## 1214 50031 23/09/2014 23 9 2014 52.83075 -1.9289073 404887
## 1215 50031 23/09/2015 23 9 2015 52.83075 -1.9289073 404887
## 1216 50031 24/03/1987 24 3 1987 52.83075 -1.9289073 404887
## 1217 50031 24/06/1986 24 6 1986 52.83075 -1.9289073 404887
## 1218 50031 25/02/1988 25 2 1988 52.83075 -1.9289073 404887
## 1219 50031 26/02/1999 26 2 1999 52.83075 -1.9289073 404887
## 1220 50031 26/04/2002 26 4 2002 52.83075 -1.9289073 404887
## 1221 50031 27/05/1997 27 5 1997 52.83075 -1.9289073 404887
## 1222 50031 27/09/1996 27 9 1996 52.83075 -1.9289073 404887
## 1223 50031 28/04/2004 28 4 2004 52.83075 -1.9289073 404887
## 1224 50031 28/09/2010 28 9 2010 52.83075 -1.9289073 404887
## 1225 50031 29/06/1987 29 6 1987 52.83075 -1.9289073 404887
## 1226 50031 29/07/1991 29 7 1991 52.83075 -1.9289073 404887
## 1227 50031 29/09/1992 29 9 1992 52.83075 -1.9289073 404887
## 1228 50031 29/10/2003 29 10 2003 52.83075 -1.9289073 404887
## 1229 50031 30/03/1993 30 3 1993 52.83075 -1.9289073 404887
## 1230 50031 30/06/1987 30 6 1987 52.83075 -1.9289073 404887
## 1231 50031 30/10/2007 30 10 2007 52.83075 -1.9289073 404887
## 1232 50031 30/11/1989 30 11 1989 52.83075 -1.9289073 404887
## 1233 50031 31/10/1991 31 10 1991 52.83075 -1.9289073 404887
## 1234 50031 31/10/2012 31 10 2012 52.83075 -1.9289073 404887
## 1235 50139 01/09/2016 1 9 2016 52.74768 -2.8320178 343934
## 1236 50139 02/09/2015 2 9 2015 52.74768 -2.8320178 343934
## 1237 50139 02/11/2010 2 11 2010 52.74768 -2.8320178 343934
## 1238 50139 03/04/1995 3 4 1995 52.74768 -2.8320178 343934
## 1239 50139 03/10/2017 3 10 2017 52.74768 -2.8320178 343934
## 1240 50139 04/08/2006 4 8 2006 52.74768 -2.8320178 343934
## 1241 50139 04/12/1997 4 12 1997 52.74768 -2.8320178 343934
## 1242 50139 05/04/2007 5 4 2007 52.74768 -2.8320178 343934
## 1243 50139 05/11/1992 5 11 1992 52.74768 -2.8320178 343934
## 1244 50139 06/04/1993 6 4 1993 52.74768 -2.8320178 343934
## 1245 50139 07/04/2010 7 4 2010 52.74768 -2.8320178 343934
## 1246 50139 07/05/1991 7 5 1991 52.74768 -2.8320178 343934
## 1247 50139 07/08/2007 7 8 2007 52.74768 -2.8320178 343934
## 1248 50139 07/10/2009 7 10 2009 52.74768 -2.8320178 343934
## 1249 50139 08/07/1988 8 7 1988 52.74768 -2.8320178 343934
## 1250 50139 08/07/1997 8 7 1997 52.74768 -2.8320178 343934
## 1251 50139 09/03/2015 9 3 2015 52.74768 -2.8320178 343934
## 1252 50139 09/04/2013 9 4 2013 52.74768 -2.8320178 343934
## 1253 50139 09/05/2017 9 5 2017 52.74768 -2.8320178 343934
## 1254 50139 09/08/2010 9 8 2010 52.74768 -2.8320178 343934
## 1255 50139 09/10/1995 9 10 1995 52.74768 -2.8320178 343934
## 1256 50139 10/05/2011 10 5 2011 52.74768 -2.8320178 343934
## 1257 50139 11/09/2018 11 9 2018 52.74768 -2.8320178 343934
## 1258 50139 11/10/2012 11 10 2012 52.74768 -2.8320178 343934
## 1259 50139 12/09/2003 12 9 2003 52.74768 -2.8320178 343934
## 1260 50139 13/07/2009 13 7 2009 52.74768 -2.8320178 343934
## 1261 50139 13/10/1998 13 10 1998 52.74768 -2.8320178 343934
## 1262 50139 15/05/1998 15 5 1998 52.74768 -2.8320178 343934
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## 1264 50139 15/10/2007 15 10 2007 52.74768 -2.8320178 343934
## 1265 50139 16/04/2003 16 4 2003 52.74768 -2.8320178 343934
## 1266 50139 17/03/2014 17 3 2014 52.74768 -2.8320178 343934
## 1267 50139 17/10/2001 17 10 2001 52.74768 -2.8320178 343934
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## 1269 50139 18/06/1993 18 6 1993 52.74768 -2.8320178 343934
## 1270 50139 18/08/2008 18 8 2008 52.74768 -2.8320178 343934
## 1271 50139 18/09/2013 18 9 2013 52.74768 -2.8320178 343934
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## 1275 50139 19/04/2006 19 4 2006 52.74768 -2.8320178 343934
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## 1278 50139 21/09/2006 21 9 2006 52.74768 -2.8320178 343934
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## 1283 50139 22/05/2018 22 5 2018 52.74768 -2.8320178 343934
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## 1288 50139 25/04/1996 25 4 1996 52.74768 -2.8320178 343934
## 1289 50139 25/06/1991 25 6 1991 52.74768 -2.8320178 343934
## 1290 50139 25/10/1989 25 10 1989 52.74768 -2.8320178 343934
## 1291 50139 28/11/1996 28 11 1996 52.74768 -2.8320178 343934
## 1292 50139 29/10/2014 29 10 2014 52.74768 -2.8320178 343934
## 1293 50139 30/03/2000 30 3 2000 52.74768 -2.8320178 343934
## 1294 50139 30/07/1990 30 7 1990 52.74768 -2.8320178 343934
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## 1298 50257 02/08/2006 2 8 2006 52.73234 -2.8425958 343200
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## 1300 50257 04/04/2002 4 4 2002 52.73234 -2.8425958 343200
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## 1304 50257 05/05/2011 5 5 2011 52.73234 -2.8425958 343200
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## 1307 50257 07/05/1991 7 5 1991 52.73234 -2.8425958 343200
## 1308 50257 07/07/1997 7 7 1997 52.73234 -2.8425958 343200
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## 1317 50257 13/10/2009 13 10 2009 52.73234 -2.8425958 343200
## 1318 50257 14/08/1995 14 8 1995 52.73234 -2.8425958 343200
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## 1324 50257 18/10/2010 18 10 2010 52.73234 -2.8425958 343200
## 1325 50257 19/03/2009 19 3 2009 52.73234 -2.8425958 343200
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## 1328 50257 20/07/2010 20 7 2010 52.73234 -2.8425958 343200
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## 1335 50257 23/10/1991 23 10 1991 52.73234 -2.8425958 343200
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## 1337 50257 24/12/2001 24 12 2001 52.73234 -2.8425958 343200
## 1338 50257 25/04/1991 25 4 1991 52.73234 -2.8425958 343200
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## 1342 50257 29/03/1993 29 3 1993 52.73234 -2.8425958 343200
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## 1407 50440 28/10/1997 28 10 1997 53.00934 -1.7659423 415802
## 1408 50440 29/08/1985 29 8 1985 53.00934 -1.7659423 415802
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## 1414 50440 31/10/2012 31 10 2012 53.00934 -1.7659423 415802
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## 1427 50766 10/08/2009 10 8 2009 52.79821 -3.1250671 324241
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## 1436 50766 14/03/2011 14 3 2011 52.79821 -3.1250671 324241
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## 1444 50766 17/09/1998 17 9 1998 52.79821 -3.1250671 324241
## 1445 50766 18/06/1997 18 6 1997 52.79821 -3.1250671 324241
## 1446 50766 18/06/2015 18 6 2015 52.79821 -3.1250671 324241
## 1447 50766 18/11/2013 18 11 2013 52.79821 -3.1250671 324241
## 1448 50766 19/05/2016 19 5 2016 52.79821 -3.1250671 324241
## 1449 50766 19/07/2016 19 7 2016 52.79821 -3.1250671 324241
## 1450 50766 20/04/1999 20 4 1999 52.79821 -3.1250671 324241
## 1451 50766 20/06/2014 20 6 2014 52.79821 -3.1250671 324241
## 1452 50766 20/11/2008 20 11 2008 52.79821 -3.1250671 324241
## 1453 50766 21/04/2006 21 4 2006 52.79821 -3.1250671 324241
## 1454 50766 21/08/2008 21 8 2008 52.79821 -3.1250671 324241
## 1455 50766 22/04/2008 22 4 2008 52.79821 -3.1250671 324241
## 1456 50766 22/04/2013 22 4 2013 52.79821 -3.1250671 324241
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## 1460 50766 23/04/1990 23 4 1990 52.79821 -3.1250671 324241
## 1461 50766 23/11/1995 23 11 1995 52.79821 -3.1250671 324241
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## 1463 50766 24/10/2000 24 10 2000 52.79821 -3.1250671 324241
## 1464 50766 25/07/2018 25 7 2018 52.79821 -3.1250671 324241
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## 1466 50766 25/09/2018 25 9 2018 52.79821 -3.1250671 324241
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## 1469 50766 26/10/1988 26 10 1988 52.79821 -3.1250671 324241
## 1470 50766 27/04/2015 27 4 2015 52.79821 -3.1250671 324241
## 1471 50766 27/05/1992 27 5 1992 52.79821 -3.1250671 324241
## 1472 50766 27/06/2017 27 6 2017 52.79821 -3.1250671 324241
## 1473 50766 28/01/1997 28 1 1997 52.79821 -3.1250671 324241
## 1474 50766 28/03/2007 28 3 2007 52.79821 -3.1250671 324241
## 1475 50766 28/05/2003 28 5 2003 52.79821 -3.1250671 324241
## 1476 50766 29/05/1991 29 5 1991 52.79821 -3.1250671 324241
## 1477 50766 29/09/2010 29 9 2010 52.79821 -3.1250671 324241
## 1478 50766 30/07/1990 30 7 1990 52.79821 -3.1250671 324241
## 1479 50766 31/05/2002 31 5 2002 52.79821 -3.1250671 324241
## 1480 51064 01/07/1992 1 7 1992 52.79248 -1.4442244 437575
## 1481 51064 02/08/1989 2 8 1989 52.79248 -1.4442244 437575
## 1482 51064 02/10/1990 2 10 1990 52.79248 -1.4442244 437575
## 1483 51064 03/04/1985 3 4 1985 52.79248 -1.4442244 437575
## 1484 51064 03/04/2017 3 4 2017 52.79248 -1.4442244 437575
## 1485 51064 04/10/1993 4 10 1993 52.79248 -1.4442244 437575
## 1486 51064 05/03/1990 5 3 1990 52.79248 -1.4442244 437575
## 1487 51064 05/09/1994 5 9 1994 52.79248 -1.4442244 437575
## 1488 51064 05/10/1987 5 10 1987 52.79248 -1.4442244 437575
## 1489 51064 06/03/1995 6 3 1995 52.79248 -1.4442244 437575
## 1490 51064 07/02/1994 7 2 1994 52.79248 -1.4442244 437575
## 1491 51064 08/02/1993 8 2 1993 52.79248 -1.4442244 437575
## 1492 51064 08/10/1998 8 10 1998 52.79248 -1.4442244 437575
## 1493 51064 08/12/1987 8 12 1987 52.79248 -1.4442244 437575
## 1494 51064 08/12/1988 8 12 1988 52.79248 -1.4442244 437575
## 1495 51064 09/05/2018 9 5 2018 52.79248 -1.4442244 437575
## 1496 51064 09/09/2016 9 9 2016 52.79248 -1.4442244 437575
## 1497 51064 10/09/1991 10 9 1991 52.79248 -1.4442244 437575
## 1498 51064 11/03/1991 11 3 1991 52.79248 -1.4442244 437575
## 1499 51064 12/04/2007 12 4 2007 52.79248 -1.4442244 437575
## 1500 51064 12/12/1985 12 12 1985 52.79248 -1.4442244 437575
## 1501 51064 13/05/2004 13 5 2004 52.79248 -1.4442244 437575
## 1502 51064 13/10/2017 13 10 2017 52.79248 -1.4442244 437575
## 1503 51064 14/02/1992 14 2 1992 52.79248 -1.4442244 437575
## 1504 51064 14/03/2000 14 3 2000 52.79248 -1.4442244 437575
## 1505 51064 14/06/1994 14 6 1994 52.79248 -1.4442244 437575
## 1506 51064 14/08/1985 14 8 1985 52.79248 -1.4442244 437575
## 1507 51064 14/10/1986 14 10 1986 52.79248 -1.4442244 437575
## 1508 51064 15/12/1986 15 12 1986 52.79248 -1.4442244 437575
## 1509 51064 16/06/1993 16 6 1993 52.79248 -1.4442244 437575
## 1510 51064 16/07/1986 16 7 1986 52.79248 -1.4442244 437575
## 1511 51064 16/09/1992 16 9 1992 52.79248 -1.4442244 437575
## 1512 51064 18/09/2018 18 9 2018 52.79248 -1.4442244 437575
## 1513 51064 19/03/1996 19 3 1996 52.79248 -1.4442244 437575
## 1514 51064 19/04/2016 19 4 2016 52.79248 -1.4442244 437575
## 1515 51064 19/05/1988 19 5 1988 52.79248 -1.4442244 437575
## 1516 51064 19/05/1999 19 5 1999 52.79248 -1.4442244 437575
## 1517 51064 19/06/1991 19 6 1991 52.79248 -1.4442244 437575
## 1518 51064 20/03/1986 20 3 1986 52.79248 -1.4442244 437575
## 1519 51064 20/11/2007 20 11 2007 52.79248 -1.4442244 437575
## 1520 51064 21/07/1990 21 7 1990 52.79248 -1.4442244 437575
## 1521 51064 22/06/1987 22 6 1987 52.79248 -1.4442244 437575
## 1522 51064 22/09/1995 22 9 1995 52.79248 -1.4442244 437575
## 1523 51064 22/09/1997 22 9 1997 52.79248 -1.4442244 437575
## 1524 51064 22/11/2000 22 11 2000 52.79248 -1.4442244 437575
## 1525 51064 25/05/2006 25 5 2006 52.79248 -1.4442244 437575
## 1526 51064 25/10/2013 25 10 2013 52.79248 -1.4442244 437575
## 1527 51064 27/02/1997 27 2 1997 52.79248 -1.4442244 437575
## 1528 51064 27/05/1998 27 5 1998 52.79248 -1.4442244 437575
## 1529 51064 27/10/2004 27 10 2004 52.79248 -1.4442244 437575
## 1530 51064 29/04/2002 29 4 2002 52.79248 -1.4442244 437575
## 1531 51064 29/04/2013 29 4 2013 52.79248 -1.4442244 437575
## 1532 51064 31/10/2006 31 10 2006 52.79248 -1.4442244 437575
## 1533 51065 01/07/1992 1 7 1992 52.79089 -1.4414271 437765
## 1534 51065 02/08/1989 2 8 1989 52.79089 -1.4414271 437765
## 1535 51065 02/09/2015 2 9 2015 52.79089 -1.4414271 437765
## 1536 51065 03/04/1985 3 4 1985 52.79089 -1.4414271 437765
## 1537 51065 03/04/2017 3 4 2017 52.79089 -1.4414271 437765
## 1538 51065 04/10/1993 4 10 1993 52.79089 -1.4414271 437765
## 1539 51065 05/03/1990 5 3 1990 52.79089 -1.4414271 437765
## 1540 51065 05/09/1994 5 9 1994 52.79089 -1.4414271 437765
## 1541 51065 05/10/1987 5 10 1987 52.79089 -1.4414271 437765
## 1542 51065 06/03/1995 6 3 1995 52.79089 -1.4414271 437765
## 1543 51065 06/05/2003 6 5 2003 52.79089 -1.4414271 437765
## 1544 51065 06/06/1993 6 6 1993 52.79089 -1.4414271 437765
## 1545 51065 07/02/1994 7 2 1994 52.79089 -1.4414271 437765
## 1546 51065 08/02/1993 8 2 1993 52.79089 -1.4414271 437765
## 1547 51065 08/10/1998 8 10 1998 52.79089 -1.4414271 437765
## 1548 51065 08/12/1987 8 12 1987 52.79089 -1.4414271 437765
## 1549 51065 08/12/1988 8 12 1988 52.79089 -1.4414271 437765
## 1550 51065 09/05/2018 9 5 2018 52.79089 -1.4414271 437765
## 1551 51065 09/09/2016 9 9 2016 52.79089 -1.4414271 437765
## 1552 51065 10/09/1991 10 9 1991 52.79089 -1.4414271 437765
## 1553 51065 10/10/1990 10 10 1990 52.79089 -1.4414271 437765
## 1554 51065 11/03/1991 11 3 1991 52.79089 -1.4414271 437765
## 1555 51065 11/10/2013 11 10 2013 52.79089 -1.4414271 437765
## 1556 51065 12/11/2014 12 11 2014 52.79089 -1.4414271 437765
## 1557 51065 12/12/1985 12 12 1985 52.79089 -1.4414271 437765
## 1558 51065 13/03/1996 13 3 1996 52.79089 -1.4414271 437765
## 1559 51065 13/10/2017 13 10 2017 52.79089 -1.4414271 437765
## 1560 51065 14/02/1992 14 2 1992 52.79089 -1.4414271 437765
## 1561 51065 14/03/2000 14 3 2000 52.79089 -1.4414271 437765
## 1562 51065 14/06/1994 14 6 1994 52.79089 -1.4414271 437765
## 1563 51065 14/08/1985 14 8 1985 52.79089 -1.4414271 437765
## 1564 51065 14/10/2003 14 10 2003 52.79089 -1.4414271 437765
## 1565 51065 15/12/1986 15 12 1986 52.79089 -1.4414271 437765
## 1566 51065 16/07/1986 16 7 1986 52.79089 -1.4414271 437765
## 1567 51065 16/09/1992 16 9 1992 52.79089 -1.4414271 437765
## 1568 51065 16/11/2012 16 11 2012 52.79089 -1.4414271 437765
## 1569 51065 17/12/1996 17 12 1996 52.79089 -1.4414271 437765
## 1570 51065 18/09/2018 18 9 2018 52.79089 -1.4414271 437765
## 1571 51065 19/04/2016 19 4 2016 52.79089 -1.4414271 437765
## 1572 51065 19/05/1988 19 5 1988 52.79089 -1.4414271 437765
## 1573 51065 19/06/1991 19 6 1991 52.79089 -1.4414271 437765
## 1574 51065 20/03/1986 20 3 1986 52.79089 -1.4414271 437765
## 1575 51065 21/07/1990 21 7 1990 52.79089 -1.4414271 437765
## 1576 51065 22/05/2015 22 5 2015 52.79089 -1.4414271 437765
## 1577 51065 22/06/1987 22 6 1987 52.79089 -1.4414271 437765
## 1578 51065 22/09/1995 22 9 1995 52.79089 -1.4414271 437765
## 1579 51065 22/09/1997 22 9 1997 52.79089 -1.4414271 437765
## 1580 51065 22/11/2000 22 11 2000 52.79089 -1.4414271 437765
## 1581 51065 25/05/2006 25 5 2006 52.79089 -1.4414271 437765
## 1582 51065 27/02/1997 27 2 1997 52.79089 -1.4414271 437765
## 1583 51065 27/05/1998 27 5 1998 52.79089 -1.4414271 437765
## 1584 51065 29/04/2013 29 4 2013 52.79089 -1.4414271 437765
## 1585 51065 30/11/2002 30 11 2002 52.79089 -1.4414271 437765
## 1586 51065 31/05/2012 31 5 2012 52.79089 -1.4414271 437765
## 1587 51065 31/10/2006 31 10 2006 52.79089 -1.4414271 437765
## 1588 51097 01/05/1986 1 5 1986 53.05457 -1.7992062 413556
## 1589 51097 01/05/2009 1 5 2009 53.05457 -1.7992062 413556
## 1590 51097 02/11/2010 2 11 2010 53.05457 -1.7992062 413556
## 1591 51097 03/11/2015 3 11 2015 53.05457 -1.7992062 413556
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## 1593 51097 04/09/2014 4 9 2014 53.05457 -1.7992062 413556
## 1594 51097 06/05/2015 6 5 2015 53.05457 -1.7992062 413556
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## 1596 51097 06/10/1999 6 10 1999 53.05457 -1.7992062 413556
## 1597 51097 07/04/2006 7 4 2006 53.05457 -1.7992062 413556
## 1598 51097 07/05/2013 7 5 2013 53.05457 -1.7992062 413556
## 1599 51097 08/03/1995 8 3 1995 53.05457 -1.7992062 413556
## 1600 51097 08/09/2017 8 9 2017 53.05457 -1.7992062 413556
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## 1603 51097 11/10/1988 11 10 1988 53.05457 -1.7992062 413556
## 1604 51097 11/10/2018 11 10 2018 53.05457 -1.7992062 413556
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## 1606 51097 13/03/2000 13 3 2000 53.05457 -1.7992062 413556
## 1607 51097 13/04/1987 13 4 1987 53.05457 -1.7992062 413556
## 1608 51097 13/05/2010 13 5 2010 53.05457 -1.7992062 413556
## 1609 51097 13/05/2014 13 5 2014 53.05457 -1.7992062 413556
## 1610 51097 13/09/1995 13 9 1995 53.05457 -1.7992062 413556
## 1611 51097 13/09/2002 13 9 2002 53.05457 -1.7992062 413556
## 1612 51097 13/10/1991 13 10 1991 53.05457 -1.7992062 413556
## 1613 51097 13/11/1986 13 11 1986 53.05457 -1.7992062 413556
## 1614 51097 14/08/2012 14 8 2012 53.05457 -1.7992062 413556
## 1615 51097 14/10/2008 14 10 2008 53.05457 -1.7992062 413556
## 1616 51097 14/11/2012 14 11 2012 53.05457 -1.7992062 413556
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## 1618 51097 15/08/2011 15 8 2011 53.05457 -1.7992062 413556
## 1619 51097 16/03/1999 16 3 1999 53.05457 -1.7992062 413556
## 1620 51097 16/05/2008 16 5 2008 53.05457 -1.7992062 413556
## 1621 51097 16/05/2018 16 5 2018 53.05457 -1.7992062 413556
## 1622 51097 16/09/2003 16 9 2003 53.05457 -1.7992062 413556
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## 1624 51097 17/03/2004 17 3 2004 53.05457 -1.7992062 413556
## 1625 51097 17/04/2003 17 4 2003 53.05457 -1.7992062 413556
## 1626 51097 17/06/1997 17 6 1997 53.05457 -1.7992062 413556
## 1627 51097 18/11/1998 18 11 1998 53.05457 -1.7992062 413556
## 1628 51097 18/11/2009 18 11 2009 53.05457 -1.7992062 413556
## 1629 51097 19/02/1987 19 2 1987 53.05457 -1.7992062 413556
## 1630 51097 19/06/1990 19 6 1990 53.05457 -1.7992062 413556
## 1631 51097 20/03/1990 20 3 1990 53.05457 -1.7992062 413556
## 1632 51097 20/04/2007 20 4 2007 53.05457 -1.7992062 413556
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## 1634 51097 20/09/2001 20 9 2001 53.05457 -1.7992062 413556
## 1635 51097 20/09/2006 20 9 2006 53.05457 -1.7992062 413556
## 1636 51097 21/03/2012 21 3 2012 53.05457 -1.7992062 413556
## 1637 51097 21/04/2016 21 4 2016 53.05457 -1.7992062 413556
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## 1639 51097 21/10/2005 21 10 2005 53.05457 -1.7992062 413556
## 1640 51097 21/12/2000 21 12 2000 53.05457 -1.7992062 413556
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## 1644 51097 22/11/1993 22 11 1993 53.05457 -1.7992062 413556
## 1645 51097 23/04/2002 23 4 2002 53.05457 -1.7992062 413556
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## 1647 51097 23/09/2011 23 9 2011 53.05457 -1.7992062 413556
## 1648 51097 23/09/2016 23 9 2016 53.05457 -1.7992062 413556
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## 1651 51097 24/04/2017 24 4 2017 53.05457 -1.7992062 413556
## 1652 51097 24/10/2013 24 10 2013 53.05457 -1.7992062 413556
## 1653 51097 25/11/1985 25 11 1985 53.05457 -1.7992062 413556
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## 1655 51097 26/09/2007 26 9 2007 53.05457 -1.7992062 413556
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## 1657 51097 27/04/2011 27 4 2011 53.05457 -1.7992062 413556
## 1658 51097 28/04/2005 28 4 2005 53.05457 -1.7992062 413556
## 1659 51097 28/07/1987 28 7 1987 53.05457 -1.7992062 413556
## 1660 51097 28/10/1997 28 10 1997 53.05457 -1.7992062 413556
## 1661 51097 29/08/1985 29 8 1985 53.05457 -1.7992062 413556
## 1662 51097 30/03/1993 30 3 1993 53.05457 -1.7992062 413556
## 1663 51097 31/10/1992 31 10 1992 53.05457 -1.7992062 413556
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## 1665 51122 02/05/2000 2 5 2000 52.31290 -1.4547218 437270
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## 1667 51122 02/08/2011 2 8 2011 52.31290 -1.4547218 437270
## 1668 51122 02/09/2004 2 9 2004 52.31290 -1.4547218 437270
## 1669 51122 02/10/2017 2 10 2017 52.31290 -1.4547218 437270
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## 1676 51122 08/03/2011 8 3 2011 52.31290 -1.4547218 437270
## 1677 51122 09/05/2008 9 5 2008 52.31290 -1.4547218 437270
## 1678 51122 09/08/2012 9 8 2012 52.31290 -1.4547218 437270
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## 1681 51122 10/07/2018 10 7 2018 52.31290 -1.4547218 437270
## 1682 51122 10/10/2018 10 10 2018 52.31290 -1.4547218 437270
## 1683 51122 10/11/1993 10 11 1993 52.31290 -1.4547218 437270
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## 1687 51122 13/03/2013 13 3 2013 52.31290 -1.4547218 437270
## 1688 51122 14/11/1991 14 11 1991 52.31290 -1.4547218 437270
## 1689 51122 14/11/2006 14 11 2006 52.31290 -1.4547218 437270
## 1690 51122 15/05/2017 15 5 2017 52.31290 -1.4547218 437270
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## 1692 51122 16/08/2017 16 8 2017 52.31290 -1.4547218 437270
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## 1694 51122 18/05/2004 18 5 2004 52.31290 -1.4547218 437270
## 1695 51122 18/10/2011 18 10 2011 52.31290 -1.4547218 437270
## 1696 51122 19/05/2010 19 5 2010 52.31290 -1.4547218 437270
## 1697 51122 20/05/1997 20 5 1997 52.31290 -1.4547218 437270
## 1698 51122 20/09/2016 20 9 2016 52.31290 -1.4547218 437270
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## 1700 51122 21/10/2014 21 10 2014 52.31290 -1.4547218 437270
## 1701 51122 22/05/1995 22 5 1995 52.31290 -1.4547218 437270
## 1702 51122 22/05/2018 22 5 2018 52.31290 -1.4547218 437270
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## 1705 51122 22/10/2008 22 10 2008 52.31290 -1.4547218 437270
## 1706 51122 23/05/2014 23 5 2014 52.31290 -1.4547218 437270
## 1707 51122 23/10/1996 23 10 1996 52.31290 -1.4547218 437270
## 1708 51122 23/10/2012 23 10 2012 52.31290 -1.4547218 437270
## 1709 51122 23/12/1992 23 12 1992 52.31290 -1.4547218 437270
## 1710 51122 24/04/2007 24 4 2007 52.31290 -1.4547218 437270
## 1711 51122 24/04/2015 24 4 2015 52.31290 -1.4547218 437270
## 1712 51122 24/10/1995 24 10 1995 52.31290 -1.4547218 437270
## 1713 51122 25/04/2016 25 4 2016 52.31290 -1.4547218 437270
## 1714 51122 25/05/1999 25 5 1999 52.31290 -1.4547218 437270
## 1715 51122 25/10/2013 25 10 2013 52.31290 -1.4547218 437270
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## 1719 51357 02/05/2000 2 5 2000 53.13520 -1.8208630 412082
## 1720 51357 04/03/2003 4 3 2003 53.13520 -1.8208630 412082
## 1721 51357 04/04/2002 4 4 2002 53.13520 -1.8208630 412082
## 1722 51357 04/10/2001 4 10 2001 53.13520 -1.8208630 412082
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## 1725 51357 08/03/1995 8 3 1995 53.13520 -1.8208630 412082
## 1726 51357 08/04/1991 8 4 1991 53.13520 -1.8208630 412082
## 1727 51357 08/10/1990 8 10 1990 53.13520 -1.8208630 412082
## 1728 51357 09/05/1994 9 5 1994 53.13520 -1.8208630 412082
## 1729 51357 09/09/2010 9 9 2010 53.13520 -1.8208630 412082
## 1730 51357 10/02/1992 10 2 1992 53.13520 -1.8208630 412082
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## 1732 51357 11/10/1988 11 10 1988 53.13520 -1.8208630 412082
## 1733 51357 12/04/2006 12 4 2006 53.13520 -1.8208630 412082
## 1734 51357 12/10/2009 12 10 2009 53.13520 -1.8208630 412082
## 1735 51357 13/04/1987 13 4 1987 53.13520 -1.8208630 412082
## 1736 51357 13/09/1995 13 9 1995 53.13520 -1.8208630 412082
## 1737 51357 13/09/2002 13 9 2002 53.13520 -1.8208630 412082
## 1738 51357 13/10/1991 13 10 1991 53.13520 -1.8208630 412082
## 1739 51357 14/04/1993 14 4 1993 53.13520 -1.8208630 412082
## 1740 51357 14/10/2008 14 10 2008 53.13520 -1.8208630 412082
## 1741 51357 14/11/1983 14 11 1983 53.13520 -1.8208630 412082
## 1742 51357 14/11/2012 14 11 2012 53.13520 -1.8208630 412082
## 1743 51357 15/08/1994 15 8 1994 53.13520 -1.8208630 412082
## 1744 51357 16/03/1999 16 3 1999 53.13520 -1.8208630 412082
## 1745 51357 16/05/1996 16 5 1996 53.13520 -1.8208630 412082
## 1746 51357 16/05/2008 16 5 2008 53.13520 -1.8208630 412082
## 1747 51357 16/09/1997 16 9 1997 53.13520 -1.8208630 412082
## 1748 51357 16/11/1993 16 11 1993 53.13520 -1.8208630 412082
## 1749 51357 17/03/1998 17 3 1998 53.13520 -1.8208630 412082
## 1750 51357 17/07/1991 17 7 1991 53.13520 -1.8208630 412082
## 1751 51357 17/07/1997 17 7 1997 53.13520 -1.8208630 412082
## 1752 51357 18/10/2000 18 10 2000 53.13520 -1.8208630 412082
## 1753 51357 18/11/1998 18 11 1998 53.13520 -1.8208630 412082
## 1754 51357 19/06/1990 19 6 1990 53.13520 -1.8208630 412082
## 1755 51357 19/08/1997 19 8 1997 53.13520 -1.8208630 412082
## 1756 51357 20/04/2007 20 4 2007 53.13520 -1.8208630 412082
## 1757 51357 20/09/2006 20 9 2006 53.13520 -1.8208630 412082
## 1758 51357 21/03/2012 21 3 2012 53.13520 -1.8208630 412082
## 1759 51357 21/06/1988 21 6 1988 53.13520 -1.8208630 412082
## 1760 51357 21/11/1985 21 11 1985 53.13520 -1.8208630 412082
## 1761 51357 23/09/1996 23 9 1996 53.13520 -1.8208630 412082
## 1762 51357 24/04/1985 24 4 1985 53.13520 -1.8208630 412082
## 1763 51357 24/06/1992 24 6 1992 53.13520 -1.8208630 412082
## 1764 51357 24/09/2003 24 9 2003 53.13520 -1.8208630 412082
## 1765 51357 25/05/2011 25 5 2011 53.13520 -1.8208630 412082
## 1766 51357 25/08/1982 25 8 1982 53.13520 -1.8208630 412082
## 1767 51357 26/04/2010 26 4 2010 53.13520 -1.8208630 412082
## 1768 51357 26/07/1993 26 7 1993 53.13520 -1.8208630 412082
## 1769 51357 26/10/1987 26 10 1987 53.13520 -1.8208630 412082
## 1770 51357 27/01/2000 27 1 2000 53.13520 -1.8208630 412082
## 1771 51357 27/09/1999 27 9 1999 53.13520 -1.8208630 412082
## 1772 51357 28/10/2011 28 10 2011 53.13520 -1.8208630 412082
## 1773 51357 29/05/2015 29 5 2015 53.13520 -1.8208630 412082
## 1774 51357 31/10/1992 31 10 1992 53.13520 -1.8208630 412082
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## 1776 51392 01/06/1992 1 6 1992 52.76853 -1.8394880 410927
## 1777 51392 01/09/2016 1 9 2016 52.76853 -1.8394880 410927
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## 1779 51392 01/10/2018 1 10 2018 52.76853 -1.8394880 410927
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## 1781 51392 03/05/2018 3 5 2018 52.76853 -1.8394880 410927
## 1782 51392 03/09/2013 3 9 2013 52.76853 -1.8394880 410927
## 1783 51392 03/11/2004 3 11 2004 52.76853 -1.8394880 410927
## 1784 51392 04/05/2007 4 5 2007 52.76853 -1.8394880 410927
## 1785 51392 04/09/2002 4 9 2002 52.76853 -1.8394880 410927
## 1786 51392 05/05/2010 5 5 2010 52.76853 -1.8394880 410927
## 1787 51392 05/10/2009 5 10 2009 52.76853 -1.8394880 410927
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## 1789 51392 06/04/2016 6 4 2016 52.76853 -1.8394880 410927
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## 1791 51392 06/10/2000 6 10 2000 52.76853 -1.8394880 410927
## 1792 51392 06/11/2012 6 11 2012 52.76853 -1.8394880 410927
## 1793 51392 07/04/2003 7 4 2003 52.76853 -1.8394880 410927
## 1794 51392 08/11/1993 8 11 1993 52.76853 -1.8394880 410927
## 1795 51392 09/10/2001 9 10 2001 52.76853 -1.8394880 410927
## 1796 51392 09/10/2017 9 10 2017 52.76853 -1.8394880 410927
## 1797 51392 10/10/1997 10 10 1997 52.76853 -1.8394880 410927
## 1798 51392 10/11/1995 10 11 1995 52.76853 -1.8394880 410927
## 1799 51392 11/04/2000 11 4 2000 52.76853 -1.8394880 410927
## 1800 51392 11/04/2014 11 4 2014 52.76853 -1.8394880 410927
## 1801 51392 11/04/2017 11 4 2017 52.76853 -1.8394880 410927
## 1802 51392 12/01/2000 12 1 2000 52.76853 -1.8394880 410927
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## 1804 51392 13/08/2013 13 8 2013 52.76853 -1.8394880 410927
## 1805 51392 13/10/2011 13 10 2011 52.76853 -1.8394880 410927
## 1806 51392 14/05/2012 14 5 2012 52.76853 -1.8394880 410927
## 1807 51392 14/07/1993 14 7 1993 52.76853 -1.8394880 410927
## 1808 51392 14/09/2015 14 9 2015 52.76853 -1.8394880 410927
## 1809 51392 15/03/2005 15 3 2005 52.76853 -1.8394880 410927
## 1810 51392 15/04/1985 15 4 1985 52.76853 -1.8394880 410927
## 1811 51392 15/06/1988 15 6 1988 52.76853 -1.8394880 410927
## 1812 51392 16/02/1992 16 2 1992 52.76853 -1.8394880 410927
## 1813 51392 16/07/2018 16 7 2018 52.76853 -1.8394880 410927
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## 1815 51392 17/11/1998 17 11 1998 52.76853 -1.8394880 410927
## 1816 51392 18/04/1996 18 4 1996 52.76853 -1.8394880 410927
## 1817 51392 18/04/2011 18 4 2011 52.76853 -1.8394880 410927
## 1818 51392 18/05/1990 18 5 1990 52.76853 -1.8394880 410927
## 1819 51392 18/09/2008 18 9 2008 52.76853 -1.8394880 410927
## 1820 51392 18/12/1985 18 12 1985 52.76853 -1.8394880 410927
## 1821 51392 19/04/2002 19 4 2002 52.76853 -1.8394880 410927
## 1822 51392 19/04/2013 19 4 2013 52.76853 -1.8394880 410927
## 1823 51392 19/07/1990 19 7 1990 52.76853 -1.8394880 410927
## 1824 51392 20/02/1991 20 2 1991 52.76853 -1.8394880 410927
## 1825 51392 20/04/2015 20 4 2015 52.76853 -1.8394880 410927
## 1826 51392 20/10/1987 20 10 1987 52.76853 -1.8394880 410927
## 1827 51392 20/10/2006 20 10 2006 52.76853 -1.8394880 410927
## 1828 51392 21/03/2006 21 3 2006 52.76853 -1.8394880 410927
## 1829 51392 21/09/2005 21 9 2005 52.76853 -1.8394880 410927
## 1830 51392 22/04/1986 22 4 1986 52.76853 -1.8394880 410927
## 1831 51392 22/05/1995 22 5 1995 52.76853 -1.8394880 410927
## 1832 51392 22/10/2007 22 10 2007 52.76853 -1.8394880 410927
## 1833 51392 23/09/2014 23 9 2014 52.76853 -1.8394880 410927
## 1834 51392 24/03/1987 24 3 1987 52.76853 -1.8394880 410927
## 1835 51392 25/02/1988 25 2 1988 52.76853 -1.8394880 410927
## 1836 51392 26/02/1999 26 2 1999 52.76853 -1.8394880 410927
## 1837 51392 26/03/1998 26 3 1998 52.76853 -1.8394880 410927
## 1838 51392 26/03/2009 26 3 2009 52.76853 -1.8394880 410927
## 1839 51392 27/05/1997 27 5 1997 52.76853 -1.8394880 410927
## 1840 51392 27/06/2017 27 6 2017 52.76853 -1.8394880 410927
## 1841 51392 27/09/1982 27 9 1982 52.76853 -1.8394880 410927
## 1842 51392 28/04/2004 28 4 2004 52.76853 -1.8394880 410927
## 1843 51392 28/09/2010 28 9 2010 52.76853 -1.8394880 410927
## 1844 51392 29/07/1991 29 7 1991 52.76853 -1.8394880 410927
## 1845 51392 29/09/1992 29 9 1992 52.76853 -1.8394880 410927
## 1846 51392 29/10/2003 29 10 2003 52.76853 -1.8394880 410927
## 1847 51392 30/03/1993 30 3 1993 52.76853 -1.8394880 410927
## 1848 51392 30/03/1994 30 3 1994 52.76853 -1.8394880 410927
## 1849 51392 30/11/1989 30 11 1989 52.76853 -1.8394880 410927
## 1850 51392 31/10/1991 31 10 1991 52.76853 -1.8394880 410927
## 1851 51634 01/05/2013 1 5 2013 53.27915 -0.9393195 470821
## 1852 51634 01/10/2003 1 10 2003 53.27915 -0.9393195 470821
## 1853 51634 03/05/2001 3 5 2001 53.27915 -0.9393195 470821
## 1854 51634 04/09/1986 4 9 1986 53.27915 -0.9393195 470821
## 1855 51634 05/02/1993 5 2 1993 53.27915 -0.9393195 470821
## 1856 51634 05/08/1992 5 8 1992 53.27915 -0.9393195 470821
## 1857 51634 05/11/1995 5 11 1995 53.27915 -0.9393195 470821
## 1858 51634 06/08/1987 6 8 1987 53.27915 -0.9393195 470821
## 1859 51634 07/03/1989 7 3 1989 53.27915 -0.9393195 470821
## 1860 51634 07/07/1993 7 7 1993 53.27915 -0.9393195 470821
## 1861 51634 07/10/1992 7 10 1992 53.27915 -0.9393195 470821
## 1862 51634 08/10/2007 8 10 2007 53.27915 -0.9393195 470821
## 1863 51634 09/04/1991 9 4 1991 53.27915 -0.9393195 470821
## 1864 51634 09/07/1991 9 7 1991 53.27915 -0.9393195 470821
## 1865 51634 09/09/2000 9 9 2000 53.27915 -0.9393195 470821
## 1866 51634 10/12/1999 10 12 1999 53.27915 -0.9393195 470821
## 1867 51634 11/03/1985 11 3 1985 53.27915 -0.9393195 470821
## 1868 51634 11/06/1994 11 6 1994 53.27915 -0.9393195 470821
## 1869 51634 11/09/1985 11 9 1985 53.27915 -0.9393195 470821
## 1870 51634 11/09/2015 11 9 2015 53.27915 -0.9393195 470821
## 1871 51634 11/10/2005 11 10 2005 53.27915 -0.9393195 470821
## 1872 51634 13/03/1992 13 3 1992 53.27915 -0.9393195 470821
## 1873 51634 13/03/1997 13 3 1997 53.27915 -0.9393195 470821
## 1874 51634 13/05/1998 13 5 1998 53.27915 -0.9393195 470821
## 1875 51634 13/05/2002 13 5 2002 53.27915 -0.9393195 470821
## 1876 51634 13/10/2008 13 10 2008 53.27915 -0.9393195 470821
## 1877 51634 15/04/2003 15 4 2003 53.27915 -0.9393195 470821
## 1878 51634 15/10/1991 15 10 1991 53.27915 -0.9393195 470821
## 1879 51634 16/09/2013 16 9 2013 53.27915 -0.9393195 470821
## 1880 51634 17/04/1995 17 4 1995 53.27915 -0.9393195 470821
## 1881 51634 17/04/2007 17 4 2007 53.27915 -0.9393195 470821
## 1882 51634 17/09/1998 17 9 1998 53.27915 -0.9393195 470821
## 1883 51634 18/05/2000 18 5 2000 53.27915 -0.9393195 470821
## 1884 51634 18/10/2006 18 10 2006 53.27915 -0.9393195 470821
## 1885 51634 19/02/1987 19 2 1987 53.27915 -0.9393195 470821
## 1886 51634 19/04/1994 19 4 1994 53.27915 -0.9393195 470821
## 1887 51634 19/11/1997 19 11 1997 53.27915 -0.9393195 470821
## 1888 51634 20/09/1989 20 9 1989 53.27915 -0.9393195 470821
## 1889 51634 20/10/1994 20 10 1994 53.27915 -0.9393195 470821
## 1890 51634 21/04/2005 21 4 2005 53.27915 -0.9393195 470821
## 1891 51634 22/03/1988 22 3 1988 53.27915 -0.9393195 470821
## 1892 51634 22/04/2009 22 4 2009 53.27915 -0.9393195 470821
## 1893 51634 22/09/1988 22 9 1988 53.27915 -0.9393195 470821
## 1894 51634 22/09/2004 22 9 2004 53.27915 -0.9393195 470821
## 1895 51634 22/11/1996 22 11 1996 53.27915 -0.9393195 470821
## 1896 51634 23/04/2004 23 4 2004 53.27915 -0.9393195 470821
## 1897 51634 24/02/1986 24 2 1986 53.27915 -0.9393195 470821
## 1898 51634 25/04/2008 25 4 2008 53.27915 -0.9393195 470821
## 1899 51634 26/11/1990 26 11 1990 53.27915 -0.9393195 470821
## 1900 51634 27/03/1990 27 3 1990 53.27915 -0.9393195 470821
## 1901 51634 27/04/2006 27 4 2006 53.27915 -0.9393195 470821
## 1902 51634 27/04/2015 27 4 2015 53.27915 -0.9393195 470821
## 1903 51634 28/11/2002 28 11 2002 53.27915 -0.9393195 470821
## 1904 51634 30/08/1990 30 8 1990 53.27915 -0.9393195 470821
## 1905 51634 30/09/2009 30 9 2009 53.27915 -0.9393195 470821
## 1906 52265 01/12/1988 1 12 1988 53.14999 -1.4632911 435992
## 1907 52265 02/07/1997 2 7 1997 53.14999 -1.4632911 435992
## 1908 52265 02/10/2002 2 10 2002 53.14999 -1.4632911 435992
## 1909 52265 02/10/2013 2 10 2013 53.14999 -1.4632911 435992
## 1910 52265 03/06/1986 3 6 1986 53.14999 -1.4632911 435992
## 1911 52265 03/10/1994 3 10 1994 53.14999 -1.4632911 435992
## 1912 52265 04/01/1988 4 1 1988 53.14999 -1.4632911 435992
## 1913 52265 04/02/1987 4 2 1987 53.14999 -1.4632911 435992
## 1914 52265 04/05/2010 4 5 2010 53.14999 -1.4632911 435992
## 1915 52265 05/03/1985 5 3 1985 53.14999 -1.4632911 435992
## 1916 52265 05/10/2010 5 10 2010 53.14999 -1.4632911 435992
## 1917 52265 07/03/1990 7 3 1990 53.14999 -1.4632911 435992
## 1918 52265 07/05/2013 7 5 2013 53.14999 -1.4632911 435992
## 1919 52265 08/03/1995 8 3 1995 53.14999 -1.4632911 435992
## 1920 52265 09/04/2015 9 4 2015 53.14999 -1.4632911 435992
## 1921 52265 11/03/1991 11 3 1991 53.14999 -1.4632911 435992
## 1922 52265 11/06/1991 11 6 1991 53.14999 -1.4632911 435992
## 1923 52265 11/12/1996 11 12 1996 53.14999 -1.4632911 435992
## 1924 52265 12/10/1995 12 10 1995 53.14999 -1.4632911 435992
## 1925 52265 12/11/1998 12 11 1998 53.14999 -1.4632911 435992
## 1926 52265 13/10/2015 13 10 2015 53.14999 -1.4632911 435992
## 1927 52265 14/06/1990 14 6 1990 53.14999 -1.4632911 435992
## 1928 52265 15/03/2016 15 3 2016 53.14999 -1.4632911 435992
## 1929 52265 17/02/1993 17 2 1993 53.14999 -1.4632911 435992
## 1930 52265 17/03/1998 17 3 1998 53.14999 -1.4632911 435992
## 1931 52265 18/01/1989 18 1 1989 53.14999 -1.4632911 435992
## 1932 52265 18/05/2007 18 5 2007 53.14999 -1.4632911 435992
## 1933 52265 18/09/1991 18 9 1991 53.14999 -1.4632911 435992
## 1934 52265 19/02/1992 19 2 1992 53.14999 -1.4632911 435992
## 1935 52265 19/10/2004 19 10 2004 53.14999 -1.4632911 435992
## 1936 52265 19/11/1985 19 11 1985 53.14999 -1.4632911 435992
## 1937 52265 20/07/1989 20 7 1989 53.14999 -1.4632911 435992
## 1938 52265 20/07/1992 20 7 1992 53.14999 -1.4632911 435992
## 1939 52265 21/06/1993 21 6 1993 53.14999 -1.4632911 435992
## 1940 52265 21/09/1992 21 9 1992 53.14999 -1.4632911 435992
## 1941 52265 21/10/1997 21 10 1997 53.14999 -1.4632911 435992
## 1942 52265 22/02/1994 22 2 1994 53.14999 -1.4632911 435992
## 1943 52265 23/09/1993 23 9 1993 53.14999 -1.4632911 435992
## 1944 52265 24/05/2000 24 5 2000 53.14999 -1.4632911 435992
## 1945 52265 24/09/2018 24 9 2018 53.14999 -1.4632911 435992
## 1946 52265 24/10/2016 24 10 2016 53.14999 -1.4632911 435992
## 1947 52265 25/09/1990 25 9 1990 53.14999 -1.4632911 435992
## 1948 52265 25/10/2007 25 10 2007 53.14999 -1.4632911 435992
## 1949 52265 26/04/1996 26 4 1996 53.14999 -1.4632911 435992
## 1950 52265 26/11/2013 26 11 2013 53.14999 -1.4632911 435992
## 1951 52265 27/10/1999 27 10 1999 53.14999 -1.4632911 435992
## 1952 52265 29/03/2004 29 3 2004 53.14999 -1.4632911 435992
## 1953 52265 29/06/1994 29 6 1994 53.14999 -1.4632911 435992
## 1954 52265 29/07/1985 29 7 1985 53.14999 -1.4632911 435992
## 1955 52265 30/04/1985 30 4 1985 53.14999 -1.4632911 435992
## 1956 52265 30/05/2018 30 5 2018 53.14999 -1.4632911 435992
## 1957 52265 30/06/1988 30 6 1988 53.14999 -1.4632911 435992
## 1958 52265 30/11/2000 30 11 2000 53.14999 -1.4632911 435992
## 1959 52265 30/11/2001 30 11 2001 53.14999 -1.4632911 435992
## 1960 52480 01/10/2004 1 10 2004 53.23426 -1.1604726 456134
## 1961 52480 02/04/2004 2 4 2004 53.23426 -1.1604726 456134
## 1962 52480 03/04/1995 3 4 1995 53.23426 -1.1604726 456134
## 1963 52480 03/05/2001 3 5 2001 53.23426 -1.1604726 456134
## 1964 52480 03/10/1989 3 10 1989 53.23426 -1.1604726 456134
## 1965 52480 03/11/1993 3 11 1993 53.23426 -1.1604726 456134
## 1966 52480 04/05/2006 4 5 2006 53.23426 -1.1604726 456134
## 1967 52480 04/10/2001 4 10 2001 53.23426 -1.1604726 456134
## 1968 52480 05/04/2007 5 4 2007 53.23426 -1.1604726 456134
## 1969 52480 05/05/1993 5 5 1993 53.23426 -1.1604726 456134
## 1970 52480 05/05/2015 5 5 2015 53.23426 -1.1604726 456134
## 1971 52480 05/08/1992 5 8 1992 53.23426 -1.1604726 456134
## 1972 52480 06/05/2010 6 5 2010 53.23426 -1.1604726 456134
## 1973 52480 06/11/1985 6 11 1985 53.23426 -1.1604726 456134
## 1974 52480 07/05/2008 7 5 2008 53.23426 -1.1604726 456134
## 1975 52480 07/05/2014 7 5 2014 53.23426 -1.1604726 456134
## 1976 52480 07/10/2010 7 10 2010 53.23426 -1.1604726 456134
## 1977 52480 08/08/1990 8 8 1990 53.23426 -1.1604726 456134
## 1978 52480 09/05/1994 9 5 1994 53.23426 -1.1604726 456134
## 1979 52480 10/07/1996 10 7 1996 53.23426 -1.1604726 456134
## 1980 52480 10/08/1993 10 8 1993 53.23426 -1.1604726 456134
## 1981 52480 10/11/1987 10 11 1987 53.23426 -1.1604726 456134
## 1982 52480 12/05/1988 12 5 1988 53.23426 -1.1604726 456134
## 1983 52480 12/06/1986 12 6 1986 53.23426 -1.1604726 456134
## 1984 52480 12/08/1997 12 8 1997 53.23426 -1.1604726 456134
## 1985 52480 12/11/1986 12 11 1986 53.23426 -1.1604726 456134
## 1986 52480 13/09/1999 13 9 1999 53.23426 -1.1604726 456134
## 1987 52480 13/10/2005 13 10 2005 53.23426 -1.1604726 456134
## 1988 52480 13/10/2009 13 10 2009 53.23426 -1.1604726 456134
## 1989 52480 14/11/1995 14 11 1995 53.23426 -1.1604726 456134
## 1990 52480 15/03/2002 15 3 2002 53.23426 -1.1604726 456134
## 1991 52480 16/03/2005 16 3 2005 53.23426 -1.1604726 456134
## 1992 52480 16/04/2003 16 4 2003 53.23426 -1.1604726 456134
## 1993 52480 16/11/1990 16 11 1990 53.23426 -1.1604726 456134
## 1994 52480 16/11/1992 16 11 1992 53.23426 -1.1604726 456134
## 1995 52480 17/09/2008 17 9 2008 53.23426 -1.1604726 456134
## 1996 52480 18/04/2018 18 4 2018 53.23426 -1.1604726 456134
## 1997 52480 18/05/2000 18 5 2000 53.23426 -1.1604726 456134
## 1998 52480 18/09/2015 18 9 2015 53.23426 -1.1604726 456134
## 1999 52480 18/10/2007 18 10 2007 53.23426 -1.1604726 456134
## 2000 52480 19/12/1996 19 12 1996 53.23426 -1.1604726 456134
## 2001 52480 20/06/1989 20 6 1989 53.23426 -1.1604726 456134
## 2002 52480 21/05/1987 21 5 1987 53.23426 -1.1604726 456134
## 2003 52480 21/05/1992 21 5 1992 53.23426 -1.1604726 456134
## 2004 52480 21/05/1998 21 5 1998 53.23426 -1.1604726 456134
## 2005 52480 21/11/1991 21 11 1991 53.23426 -1.1604726 456134
## 2006 52480 21/11/2006 21 11 2006 53.23426 -1.1604726 456134
## 2007 52480 21/12/1994 21 12 1994 53.23426 -1.1604726 456134
## 2008 52480 22/04/2009 22 4 2009 53.23426 -1.1604726 456134
## 2009 52480 23/05/1985 23 5 1985 53.23426 -1.1604726 456134
## 2010 52480 23/05/1991 23 5 1991 53.23426 -1.1604726 456134
## 2011 52480 24/10/1988 24 10 1988 53.23426 -1.1604726 456134
## 2012 52480 25/11/1998 25 11 1998 53.23426 -1.1604726 456134
## 2013 52480 25/11/2003 25 11 2003 53.23426 -1.1604726 456134
## 2014 52480 27/07/1994 27 7 1994 53.23426 -1.1604726 456134
## 2015 52480 27/11/1997 27 11 1997 53.23426 -1.1604726 456134
## 2016 52480 28/11/2000 28 11 2000 53.23426 -1.1604726 456134
## 2017 52480 30/10/2018 30 10 2018 53.23426 -1.1604726 456134
## 2018 52480 30/11/2002 30 11 2002 53.23426 -1.1604726 456134
## 2019 52491 01/05/1990 1 5 1990 52.72276 -1.7166348 419236
## 2020 52491 03/04/2003 3 4 2003 52.72276 -1.7166348 419236
## 2021 52491 03/09/2008 3 9 2008 52.72276 -1.7166348 419236
## 2022 52491 03/10/1989 3 10 1989 52.72276 -1.7166348 419236
## 2023 52491 05/03/1987 5 3 1987 52.72276 -1.7166348 419236
## 2024 52491 05/03/1997 5 3 1997 52.72276 -1.7166348 419236
## 2025 52491 05/03/2013 5 3 2013 52.72276 -1.7166348 419236
## 2026 52491 05/07/1990 5 7 1990 52.72276 -1.7166348 419236
## 2027 52491 05/10/1995 5 10 1995 52.72276 -1.7166348 419236
## 2028 52491 05/10/2007 5 10 2007 52.72276 -1.7166348 419236
## 2029 52491 05/10/2009 5 10 2009 52.72276 -1.7166348 419236
## 2030 52491 06/07/1988 6 7 1988 52.72276 -1.7166348 419236
## 2031 52491 06/10/2000 6 10 2000 52.72276 -1.7166348 419236
## 2032 52491 07/10/1998 7 10 1998 52.72276 -1.7166348 419236
## 2033 52491 07/10/2003 7 10 2003 52.72276 -1.7166348 419236
## 2034 52491 07/11/1991 7 11 1991 52.72276 -1.7166348 419236
## 2035 52491 08/02/1993 8 2 1993 52.72276 -1.7166348 419236
## 2036 52491 09/05/2000 9 5 2000 52.72276 -1.7166348 419236
## 2037 52491 09/06/1994 9 6 1994 52.72276 -1.7166348 419236
## 2038 52491 10/04/1995 10 4 1995 52.72276 -1.7166348 419236
## 2039 52491 10/06/1993 10 6 1993 52.72276 -1.7166348 419236
## 2040 52491 10/09/1987 10 9 1987 52.72276 -1.7166348 419236
## 2041 52491 10/09/1997 10 9 1997 52.72276 -1.7166348 419236
## 2042 52491 11/04/2012 11 4 2012 52.72276 -1.7166348 419236
## 2043 52491 11/11/2011 11 11 2011 52.72276 -1.7166348 419236
## 2044 52491 12/12/1988 12 12 1988 52.72276 -1.7166348 419236
## 2045 52491 13/06/1994 13 6 1994 52.72276 -1.7166348 419236
## 2046 52491 14/09/2005 14 9 2005 52.72276 -1.7166348 419236
## 2047 52491 15/02/1988 15 2 1988 52.72276 -1.7166348 419236
## 2048 52491 15/06/1987 15 6 1987 52.72276 -1.7166348 419236
## 2049 52491 15/10/1990 15 10 1990 52.72276 -1.7166348 419236
## 2050 52491 15/11/2012 15 11 2012 52.72276 -1.7166348 419236
## 2051 52491 16/05/2008 16 5 2008 52.72276 -1.7166348 419236
## 2052 52491 17/02/1994 17 2 1994 52.72276 -1.7166348 419236
## 2053 52491 17/04/1989 17 4 1989 52.72276 -1.7166348 419236
## 2054 52491 17/09/2010 17 9 2010 52.72276 -1.7166348 419236
## 2055 52491 18/03/1992 18 3 1992 52.72276 -1.7166348 419236
## 2056 52491 18/06/1991 18 6 1991 52.72276 -1.7166348 419236
## 2057 52491 18/09/2002 18 9 2002 52.72276 -1.7166348 419236
## 2058 52491 19/04/2007 19 4 2007 52.72276 -1.7166348 419236
## 2059 52491 19/11/2013 19 11 2013 52.72276 -1.7166348 419236
## 2060 52491 21/09/1994 21 9 1994 52.72276 -1.7166348 419236
## 2061 52491 23/09/2004 23 9 2004 52.72276 -1.7166348 419236
## 2062 52491 24/03/1999 24 3 1999 52.72276 -1.7166348 419236
## 2063 52491 24/03/2004 24 3 2004 52.72276 -1.7166348 419236
## 2064 52491 24/03/2010 24 3 2010 52.72276 -1.7166348 419236
## 2065 52491 24/04/1996 24 4 1996 52.72276 -1.7166348 419236
## 2066 52491 24/04/2014 24 4 2014 52.72276 -1.7166348 419236
## 2067 52491 24/10/1996 24 10 1996 52.72276 -1.7166348 419236
## 2068 52491 25/05/2005 25 5 2005 52.72276 -1.7166348 419236
## 2069 52491 26/09/2001 26 9 2001 52.72276 -1.7166348 419236
## 2070 52491 28/03/2011 28 3 2011 52.72276 -1.7166348 419236
## 2071 52491 28/04/1998 28 4 1998 52.72276 -1.7166348 419236
## 2072 52491 29/09/1992 29 9 1992 52.72276 -1.7166348 419236
## 2073 52491 29/09/2014 29 9 2014 52.72276 -1.7166348 419236
## 2074 52491 30/01/1991 30 1 1991 52.72276 -1.7166348 419236
## 2075 52491 30/06/1992 30 6 1992 52.72276 -1.7166348 419236
## 2076 52491 30/09/1993 30 9 1993 52.72276 -1.7166348 419236
## 2077 52718 01/08/1990 1 8 1990 52.98496 -1.4836591 434762
## 2078 52718 02/05/1996 2 5 1996 52.98496 -1.4836591 434762
## 2079 52718 03/09/1985 3 9 1985 52.98496 -1.4836591 434762
## 2080 52718 04/11/1994 4 11 1994 52.98496 -1.4836591 434762
## 2081 52718 05/11/1990 5 11 1990 52.98496 -1.4836591 434762
## 2082 52718 06/07/1994 6 7 1994 52.98496 -1.4836591 434762
## 2083 52718 06/08/1990 6 8 1990 52.98496 -1.4836591 434762
## 2084 52718 08/07/1987 8 7 1987 52.98496 -1.4836591 434762
## 2085 52718 08/07/1991 8 7 1991 52.98496 -1.4836591 434762
## 2086 52718 10/05/1990 10 5 1990 52.98496 -1.4836591 434762
## 2087 52718 12/04/1994 12 4 1994 52.98496 -1.4836591 434762
## 2088 52718 12/05/2005 12 5 2005 52.98496 -1.4836591 434762
## 2089 52718 12/11/1987 12 11 1987 52.98496 -1.4836591 434762
## 2090 52718 13/06/1988 13 6 1988 52.98496 -1.4836591 434762
## 2091 52718 13/08/1992 13 8 1992 52.98496 -1.4836591 434762
## 2092 52718 16/03/1998 16 3 1998 52.98496 -1.4836591 434762
## 2093 52718 16/05/2014 16 5 2014 52.98496 -1.4836591 434762
## 2094 52718 16/11/2018 16 11 2018 52.98496 -1.4836591 434762
## 2095 52718 17/10/1993 17 10 1993 52.98496 -1.4836591 434762
## 2096 52718 17/10/2017 17 10 2017 52.98496 -1.4836591 434762
## 2097 52718 18/04/2008 18 4 2008 52.98496 -1.4836591 434762
## 2098 52718 18/06/1992 18 6 1992 52.98496 -1.4836591 434762
## 2099 52718 18/10/2016 18 10 2016 52.98496 -1.4836591 434762
## 2100 52718 18/11/2015 18 11 2015 52.98496 -1.4836591 434762
## 2101 52718 19/04/2016 19 4 2016 52.98496 -1.4836591 434762
## 2102 52718 20/09/1995 20 9 1995 52.98496 -1.4836591 434762
## 2103 52718 20/10/1997 20 10 1997 52.98496 -1.4836591 434762
## 2104 52718 21/06/1993 21 6 1993 52.98496 -1.4836591 434762
## 2105 52718 21/10/1991 21 10 1991 52.98496 -1.4836591 434762
## 2106 52718 21/11/1988 21 11 1988 52.98496 -1.4836591 434762
## 2107 52718 22/04/1993 22 4 1993 52.98496 -1.4836591 434762
## 2108 52718 22/05/2015 22 5 2015 52.98496 -1.4836591 434762
## 2109 52718 22/07/1986 22 7 1986 52.98496 -1.4836591 434762
## 2110 52718 23/04/1995 23 4 1995 52.98496 -1.4836591 434762
## 2111 52718 23/07/1985 23 7 1985 52.98496 -1.4836591 434762
## 2112 52718 23/09/1998 23 9 1998 52.98496 -1.4836591 434762
## 2113 52718 23/11/2005 23 11 2005 52.98496 -1.4836591 434762
## 2114 52718 24/04/1991 24 4 1991 52.98496 -1.4836591 434762
## 2115 52718 24/10/1996 24 10 1996 52.98496 -1.4836591 434762
## 2116 52718 25/04/2017 25 4 2017 52.98496 -1.4836591 434762
## 2117 52718 25/09/1989 25 9 1989 52.98496 -1.4836591 434762
## 2118 52718 26/06/1986 26 6 1986 52.98496 -1.4836591 434762
## 2119 52718 26/11/1992 26 11 1992 52.98496 -1.4836591 434762
## 2120 52718 27/07/1993 27 7 1993 52.98496 -1.4836591 434762
## 2121 52718 29/04/1992 29 4 1992 52.98496 -1.4836591 434762
## 2122 52718 29/04/1997 29 4 1997 52.98496 -1.4836591 434762
## 2123 52718 29/11/1999 29 11 1999 52.98496 -1.4836591 434762
## 2124 52718 30/03/1989 30 3 1989 52.98496 -1.4836591 434762
## 2125 52718 30/05/2018 30 5 2018 52.98496 -1.4836591 434762
## 2126 52718 30/10/2008 30 10 2008 52.98496 -1.4836591 434762
## 2127 53594 01/10/2003 1 10 2003 53.42738 -1.0141803 465602
## 2128 53594 01/11/2016 1 11 2016 53.42738 -1.0141803 465602
## 2129 53594 02/04/2014 2 4 2014 53.42738 -1.0141803 465602
## 2130 53594 02/05/2013 2 5 2013 53.42738 -1.0141803 465602
## 2131 53594 03/05/2001 3 5 2001 53.42738 -1.0141803 465602
## 2132 53594 04/09/1986 4 9 1986 53.42738 -1.0141803 465602
## 2133 53594 05/02/1993 5 2 1993 53.42738 -1.0141803 465602
## 2134 53594 05/08/1992 5 8 1992 53.42738 -1.0141803 465602
## 2135 53594 06/08/1987 6 8 1987 53.42738 -1.0141803 465602
## 2136 53594 07/03/1989 7 3 1989 53.42738 -1.0141803 465602
## 2137 53594 07/07/1993 7 7 1993 53.42738 -1.0141803 465602
## 2138 53594 07/10/1992 7 10 1992 53.42738 -1.0141803 465602
## 2139 53594 07/11/2017 7 11 2017 53.42738 -1.0141803 465602
## 2140 53594 07/11/2018 7 11 2018 53.42738 -1.0141803 465602
## 2141 53594 08/09/2011 8 9 2011 53.42738 -1.0141803 465602
## 2142 53594 08/10/2007 8 10 2007 53.42738 -1.0141803 465602
## 2143 53594 08/11/1995 8 11 1995 53.42738 -1.0141803 465602
## 2144 53594 09/04/1991 9 4 1991 53.42738 -1.0141803 465602
## 2145 53594 09/07/1991 9 7 1991 53.42738 -1.0141803 465602
## 2146 53594 09/09/2000 9 9 2000 53.42738 -1.0141803 465602
## 2147 53594 10/12/1999 10 12 1999 53.42738 -1.0141803 465602
## 2148 53594 11/03/1985 11 3 1985 53.42738 -1.0141803 465602
## 2149 53594 11/06/1994 11 6 1994 53.42738 -1.0141803 465602
## 2150 53594 11/09/1985 11 9 1985 53.42738 -1.0141803 465602
## 2151 53594 11/09/2015 11 9 2015 53.42738 -1.0141803 465602
## 2152 53594 11/10/2005 11 10 2005 53.42738 -1.0141803 465602
## 2153 53594 12/04/2010 12 4 2010 53.42738 -1.0141803 465602
## 2154 53594 13/03/1992 13 3 1992 53.42738 -1.0141803 465602
## 2155 53594 13/03/1997 13 3 1997 53.42738 -1.0141803 465602
## 2156 53594 13/05/1998 13 5 1998 53.42738 -1.0141803 465602
## 2157 53594 13/05/2002 13 5 2002 53.42738 -1.0141803 465602
## 2158 53594 13/10/2008 13 10 2008 53.42738 -1.0141803 465602
## 2159 53594 13/11/2014 13 11 2014 53.42738 -1.0141803 465602
## 2160 53594 15/04/2003 15 4 2003 53.42738 -1.0141803 465602
## 2161 53594 15/05/2009 15 5 2009 53.42738 -1.0141803 465602
## 2162 53594 15/05/2012 15 5 2012 53.42738 -1.0141803 465602
## 2163 53594 15/07/1986 15 7 1986 53.42738 -1.0141803 465602
## 2164 53594 15/10/1991 15 10 1991 53.42738 -1.0141803 465602
## 2165 53594 16/10/2013 16 10 2013 53.42738 -1.0141803 465602
## 2166 53594 17/04/1995 17 4 1995 53.42738 -1.0141803 465602
## 2167 53594 17/04/2007 17 4 2007 53.42738 -1.0141803 465602
## 2168 53594 17/09/1998 17 9 1998 53.42738 -1.0141803 465602
## 2169 53594 18/05/2000 18 5 2000 53.42738 -1.0141803 465602
## 2170 53594 18/10/2006 18 10 2006 53.42738 -1.0141803 465602
## 2171 53594 19/02/1987 19 2 1987 53.42738 -1.0141803 465602
## 2172 53594 19/04/1994 19 4 1994 53.42738 -1.0141803 465602
## 2173 53594 19/11/1997 19 11 1997 53.42738 -1.0141803 465602
## 2174 53594 20/05/1985 20 5 1985 53.42738 -1.0141803 465602
## 2175 53594 20/09/1989 20 9 1989 53.42738 -1.0141803 465602
## 2176 53594 20/09/2012 20 9 2012 53.42738 -1.0141803 465602
## 2177 53594 20/10/1994 20 10 1994 53.42738 -1.0141803 465602
## 2178 53594 21/04/2005 21 4 2005 53.42738 -1.0141803 465602
## 2179 53594 22/03/1988 22 3 1988 53.42738 -1.0141803 465602
## 2180 53594 22/05/2018 22 5 2018 53.42738 -1.0141803 465602
## 2181 53594 22/09/1988 22 9 1988 53.42738 -1.0141803 465602
## 2182 53594 22/09/2004 22 9 2004 53.42738 -1.0141803 465602
## 2183 53594 22/11/1996 22 11 1996 53.42738 -1.0141803 465602
## 2184 53594 23/03/2016 23 3 2016 53.42738 -1.0141803 465602
## 2185 53594 23/04/2004 23 4 2004 53.42738 -1.0141803 465602
## 2186 53594 24/02/1986 24 2 1986 53.42738 -1.0141803 465602
## 2187 53594 25/04/2008 25 4 2008 53.42738 -1.0141803 465602
## 2188 53594 25/10/2010 25 10 2010 53.42738 -1.0141803 465602
## 2189 53594 26/11/1990 26 11 1990 53.42738 -1.0141803 465602
## 2190 53594 27/03/1990 27 3 1990 53.42738 -1.0141803 465602
## 2191 53594 27/04/2006 27 4 2006 53.42738 -1.0141803 465602
## 2192 53594 27/04/2011 27 4 2011 53.42738 -1.0141803 465602
## 2193 53594 27/04/2015 27 4 2015 53.42738 -1.0141803 465602
## 2194 53594 27/06/1996 27 6 1996 53.42738 -1.0141803 465602
## 2195 53594 28/11/1985 28 11 1985 53.42738 -1.0141803 465602
## 2196 53594 30/05/2017 30 5 2017 53.42738 -1.0141803 465602
## 2197 53594 30/08/1990 30 8 1990 53.42738 -1.0141803 465602
## 2198 53594 30/09/2009 30 9 2009 53.42738 -1.0141803 465602
## 2199 53594 30/11/2001 30 11 2001 53.42738 -1.0141803 465602
## 2200 53846 02/10/2002 2 10 2002 53.06122 -1.4825243 434777
## 2201 53846 03/04/2002 3 4 2002 53.06122 -1.4825243 434777
## 2202 53846 03/06/1986 3 6 1986 53.06122 -1.4825243 434777
## 2203 53846 03/09/1986 3 9 1986 53.06122 -1.4825243 434777
## 2204 53846 03/10/1994 3 10 1994 53.06122 -1.4825243 434777
## 2205 53846 04/02/1985 4 2 1985 53.06122 -1.4825243 434777
## 2206 53846 04/03/1987 4 3 1987 53.06122 -1.4825243 434777
## 2207 53846 04/04/2017 4 4 2017 53.06122 -1.4825243 434777
## 2208 53846 05/03/1985 5 3 1985 53.06122 -1.4825243 434777
## 2209 53846 05/11/2018 5 11 2018 53.06122 -1.4825243 434777
## 2210 53846 06/03/1990 6 3 1990 53.06122 -1.4825243 434777
## 2211 53846 07/10/2013 7 10 2013 53.06122 -1.4825243 434777
## 2212 53846 08/04/1999 8 4 1999 53.06122 -1.4825243 434777
## 2213 53846 08/07/1987 8 7 1987 53.06122 -1.4825243 434777
## 2214 53846 08/10/2003 8 10 2003 53.06122 -1.4825243 434777
## 2215 53846 09/04/2003 9 4 2003 53.06122 -1.4825243 434777
## 2216 53846 10/10/2011 10 10 2011 53.06122 -1.4825243 434777
## 2217 53846 10/11/1998 10 11 1998 53.06122 -1.4825243 434777
## 2218 53846 11/03/1991 11 3 1991 53.06122 -1.4825243 434777
## 2219 53846 11/06/1991 11 6 1991 53.06122 -1.4825243 434777
## 2220 53846 12/10/1995 12 10 1995 53.06122 -1.4825243 434777
## 2221 53846 13/04/2011 13 4 2011 53.06122 -1.4825243 434777
## 2222 53846 13/06/1988 13 6 1988 53.06122 -1.4825243 434777
## 2223 53846 13/10/2015 13 10 2015 53.06122 -1.4825243 434777
## 2224 53846 14/06/1990 14 6 1990 53.06122 -1.4825243 434777
## 2225 53846 15/04/2014 15 4 2014 53.06122 -1.4825243 434777
## 2226 53846 15/10/1997 15 10 1997 53.06122 -1.4825243 434777
## 2227 53846 16/04/2015 16 4 2015 53.06122 -1.4825243 434777
## 2228 53846 17/02/1993 17 2 1993 53.06122 -1.4825243 434777
## 2229 53846 17/03/1998 17 3 1998 53.06122 -1.4825243 434777
## 2230 53846 17/04/1996 17 4 1996 53.06122 -1.4825243 434777
## 2231 53846 17/09/1991 17 9 1991 53.06122 -1.4825243 434777
## 2232 53846 17/10/2006 17 10 2006 53.06122 -1.4825243 434777
## 2233 53846 17/10/2017 17 10 2017 53.06122 -1.4825243 434777
## 2234 53846 18/01/1989 18 1 1989 53.06122 -1.4825243 434777
## 2235 53846 19/02/1992 19 2 1992 53.06122 -1.4825243 434777
## 2236 53846 19/09/2012 19 9 2012 53.06122 -1.4825243 434777
## 2237 53846 19/10/2014 19 10 2014 53.06122 -1.4825243 434777
## 2238 53846 19/11/1985 19 11 1985 53.06122 -1.4825243 434777
## 2239 53846 20/07/1989 20 7 1989 53.06122 -1.4825243 434777
## 2240 53846 20/07/1992 20 7 1992 53.06122 -1.4825243 434777
## 2241 53846 21/05/2013 21 5 2013 53.06122 -1.4825243 434777
## 2242 53846 21/06/1993 21 6 1993 53.06122 -1.4825243 434777
## 2243 53846 21/09/1992 21 9 1992 53.06122 -1.4825243 434777
## 2244 53846 22/02/1994 22 2 1994 53.06122 -1.4825243 434777
## 2245 53846 22/05/2012 22 5 2012 53.06122 -1.4825243 434777
## 2246 53846 22/07/1985 22 7 1985 53.06122 -1.4825243 434777
## 2247 53846 22/10/2009 22 10 2009 53.06122 -1.4825243 434777
## 2248 53846 22/11/1996 22 11 1996 53.06122 -1.4825243 434777
## 2249 53846 23/03/2006 23 3 2006 53.06122 -1.4825243 434777
## 2250 53846 23/03/2009 23 3 2009 53.06122 -1.4825243 434777
## 2251 53846 23/09/1993 23 9 1993 53.06122 -1.4825243 434777
## 2252 53846 24/03/2016 24 3 2016 53.06122 -1.4825243 434777
## 2253 53846 24/05/2000 24 5 2000 53.06122 -1.4825243 434777
## 2254 53846 25/02/1986 25 2 1986 53.06122 -1.4825243 434777
## 2255 53846 25/09/1990 25 9 1990 53.06122 -1.4825243 434777
## 2256 53846 26/06/1986 26 6 1986 53.06122 -1.4825243 434777
## 2257 53846 27/10/2016 27 10 2016 53.06122 -1.4825243 434777
## 2258 53846 27/11/1989 27 11 1989 53.06122 -1.4825243 434777
## 2259 53846 28/10/1999 28 10 1999 53.06122 -1.4825243 434777
## 2260 53846 29/03/1995 29 3 1995 53.06122 -1.4825243 434777
## 2261 53846 29/06/1994 29 6 1994 53.06122 -1.4825243 434777
## 2262 53846 30/01/1985 30 1 1985 53.06122 -1.4825243 434777
## 2263 53846 30/03/1988 30 3 1988 53.06122 -1.4825243 434777
## 2264 53846 30/04/1985 30 4 1985 53.06122 -1.4825243 434777
## 2265 53846 30/05/2018 30 5 2018 53.06122 -1.4825243 434777
## 2266 53846 30/06/1988 30 6 1988 53.06122 -1.4825243 434777
## 2267 53846 30/06/1997 30 6 1997 53.06122 -1.4825243 434777
## 2268 53846 30/11/2000 30 11 2000 53.06122 -1.4825243 434777
## 2269 53961 02/05/1990 2 5 1990 52.71466 -1.5598784 429829
## 2270 53961 02/07/1992 2 7 1992 52.71466 -1.5598784 429829
## 2271 53961 03/04/2003 3 4 2003 52.71466 -1.5598784 429829
## 2272 53961 03/12/1991 3 12 1991 52.71466 -1.5598784 429829
## 2273 53961 04/02/1993 4 2 1993 52.71466 -1.5598784 429829
## 2274 53961 04/11/2009 4 11 2009 52.71466 -1.5598784 429829
## 2275 53961 05/05/2006 5 5 2006 52.71466 -1.5598784 429829
## 2276 53961 05/10/1992 5 10 1992 52.71466 -1.5598784 429829
## 2277 53961 05/10/1995 5 10 1995 52.71466 -1.5598784 429829
## 2278 53961 06/10/2000 6 10 2000 52.71466 -1.5598784 429829
## 2279 53961 07/10/1998 7 10 1998 52.71466 -1.5598784 429829
## 2280 53961 08/06/1993 8 6 1993 52.71466 -1.5598784 429829
## 2281 53961 09/05/2000 9 5 2000 52.71466 -1.5598784 429829
## 2282 53961 09/07/1990 9 7 1990 52.71466 -1.5598784 429829
## 2283 53961 09/10/1989 9 10 1989 52.71466 -1.5598784 429829
## 2284 53961 10/04/1995 10 4 1995 52.71466 -1.5598784 429829
## 2285 53961 10/09/1997 10 9 1997 52.71466 -1.5598784 429829
## 2286 53961 11/03/2005 11 3 2005 52.71466 -1.5598784 429829
## 2287 53961 12/07/1988 12 7 1988 52.71466 -1.5598784 429829
## 2288 53961 12/10/2010 12 10 2010 52.71466 -1.5598784 429829
## 2289 53961 12/12/1988 12 12 1988 52.71466 -1.5598784 429829
## 2290 53961 13/07/1989 13 7 1989 52.71466 -1.5598784 429829
## 2291 53961 14/02/1994 14 2 1994 52.71466 -1.5598784 429829
## 2292 53961 14/06/1994 14 6 1994 52.71466 -1.5598784 429829
## 2293 53961 15/02/1988 15 2 1988 52.71466 -1.5598784 429829
## 2294 53961 15/05/2002 15 5 2002 52.71466 -1.5598784 429829
## 2295 53961 15/05/2012 15 5 2012 52.71466 -1.5598784 429829
## 2296 53961 15/10/1990 15 10 1990 52.71466 -1.5598784 429829
## 2297 53961 17/04/1989 17 4 1989 52.71466 -1.5598784 429829
## 2298 53961 18/03/1992 18 3 1992 52.71466 -1.5598784 429829
## 2299 53961 18/06/1991 18 6 1991 52.71466 -1.5598784 429829
## 2300 53961 18/09/2002 18 9 2002 52.71466 -1.5598784 429829
## 2301 53961 19/09/1994 19 9 1994 52.71466 -1.5598784 429829
## 2302 53961 20/03/2007 20 3 2007 52.71466 -1.5598784 429829
## 2303 53961 21/04/1997 21 4 1997 52.71466 -1.5598784 429829
## 2304 53961 21/04/1998 21 4 1998 52.71466 -1.5598784 429829
## 2305 53961 21/09/2005 21 9 2005 52.71466 -1.5598784 429829
## 2306 53961 22/10/2008 22 10 2008 52.71466 -1.5598784 429829
## 2307 53961 23/04/2014 23 4 2014 52.71466 -1.5598784 429829
## 2308 53961 23/05/2008 23 5 2008 52.71466 -1.5598784 429829
## 2309 53961 23/09/1993 23 9 1993 52.71466 -1.5598784 429829
## 2310 53961 24/03/1999 24 3 1999 52.71466 -1.5598784 429829
## 2311 53961 24/04/1996 24 4 1996 52.71466 -1.5598784 429829
## 2312 53961 24/10/1996 24 10 1996 52.71466 -1.5598784 429829
## 2313 53961 26/09/2001 26 9 2001 52.71466 -1.5598784 429829
## 2314 53961 26/09/2007 26 9 2007 52.71466 -1.5598784 429829
## 2315 53961 28/01/1991 28 1 1991 52.71466 -1.5598784 429829
## 2316 53961 29/04/2009 29 4 2009 52.71466 -1.5598784 429829
## 2317 53961 29/04/2010 29 4 2010 52.71466 -1.5598784 429829
## 2318 53961 30/09/2014 30 9 2014 52.71466 -1.5598784 429829
## 2319 53961 30/10/2012 30 10 2012 52.71466 -1.5598784 429829
## Northing distinct_families MY.DATE1 julian day_in_year julian36minus
## 1 356712 10 09/01/1992 8279 245 8243
## 2 356712 21 04/03/2012 15433 94 15397
## 3 356712 16 11/03/2016 17108 308 17072
## 4 356712 18 03/04/1991 7732 63 7696
## 5 356712 20 03/04/2013 15768 63 15732
## 6 356712 20 04/04/2006 13242 94 13206
## 7 356712 21 09/04/1991 7916 247 7880
## 8 356712 25 02/05/1998 10262 36 10226
## 9 356712 26 09/05/1994 9013 248 8977
## 10 356712 24 09/06/1995 9379 249 9343
## 11 356712 17 10/06/1986 6122 279 6086
## 12 356712 24 04/07/2011 15071 97 15035
## 13 356712 14 10/07/2013 15985 280 15949
## 14 356712 17 11/07/1989 7250 311 7214
## 15 356712 21 09/08/1987 6459 251 6423
## 16 356712 20 09/08/1993 8651 251 8615
## 17 356712 23 03/09/1994 8833 68 8797
## 18 356712 10 04/09/2015 16534 99 16498
## 19 356712 13 05/09/2002 11816 129 11780
## 20 356712 27 10/09/1996 9778 283 9742
## 21 356712 21 10/09/1998 10508 282 10472
## 22 356712 17 10/09/2002 11969 282 11933
## 23 356712 20 10/10/2005 13066 283 13030
## 24 356712 18 04/11/1996 9597 102 9561
## 25 356712 16 05/11/2001 11453 131 11417
## 26 356712 11 05/11/2005 12914 131 12878
## 27 356712 11 05/11/2010 14740 131 14704
## 28 356712 17 06/11/1991 7831 162 7795
## 29 356712 21 10/11/2011 15258 284 15222
## 30 356712 17 09/13/2012 15596 257 15560
## 31 356712 17 03/14/1990 7377 73 7341
## 32 356712 23 07/15/1988 6770 197 6734
## 33 356712 29 10/16/1997 10150 289 10114
## 34 356712 18 09/17/1990 7564 260 7528
## 35 356712 19 11/17/2017 17487 321 17451
## 36 356712 17 03/19/2009 14322 78 14286
## 37 356712 21 09/19/1985 5740 262 5704
## 38 356712 25 09/19/2008 14141 263 14105
## 39 356712 13 03/20/2000 11036 80 11000
## 40 356712 20 06/20/1985 5649 171 5613
## 41 356712 19 02/21/1989 6991 52 6955
## 42 356712 17 05/21/1999 10732 141 10696
## 43 356712 16 10/21/2010 14903 294 14867
## 44 356712 18 11/21/2018 17856 325 17820
## 45 356712 10 03/22/2011 15055 81 15019
## 46 356712 17 04/22/2008 13991 113 13955
## 47 356712 16 05/22/2003 12194 142 12158
## 48 356712 19 08/22/1989 7173 234 7137
## 49 356712 26 03/23/1995 9212 82 9176
## 50 356712 15 03/23/2016 16883 83 16847
## 51 356712 19 04/23/1987 6321 113 6285
## 52 356712 24 05/23/2018 17674 143 17638
## 53 356712 18 06/23/1986 6017 174 5981
## 54 356712 13 06/23/1992 8209 175 8173
## 55 356712 29 05/25/2017 17311 145 17275
## 56 356712 16 06/25/1990 7480 176 7444
## 57 356712 22 02/26/1988 6630 57 6594
## 58 356712 13 02/26/1992 8091 57 8055
## 59 356712 16 10/26/2015 16734 299 16698
## 60 356712 25 01/27/1997 9888 27 9852
## 61 356712 17 03/27/1985 5564 86 5528
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## 2313 313091 11 09/26/2001 11591 269 11555
## 2314 313091 13 09/26/2007 13782 269 13746
## 2315 313091 7 01/28/1991 7697 28 7661
## 2316 313091 18 04/29/2009 14363 119 14327
## 2317 313091 19 04/29/2010 14728 119 14692
## 2318 313091 18 09/30/2014 16343 273 16307
## 2319 313091 20 10/30/2012 15643 304 15607
## chemical_mean BOD_mean ammonia_mean ALTITUDE alkalinity_mean
## 1 0.025000000 4.357143 0.009000000 10 167.00000
## 2 NA NA NA 10 NA
## 3 NA NA NA 10 NA
## 4 0.020000000 4.933333 0.011831000 10 150.16667
## 5 NA NA NA 10 NA
## 6 NA NA NA 10 NA
## 7 NA 3.444444 0.018790000 10 170.40000
## 8 NA 1.928571 0.006800000 10 159.71429
## 9 NA 4.166667 0.003500000 10 174.66667
## 10 NA 3.642857 0.005286000 10 175.42857
## 11 0.005500000 5.505000 0.012222000 10 152.00000
## 12 NA NA NA 10 NA
## 13 NA NA NA 10 NA
## 14 NA 4.490000 0.020163000 10 NA
## 15 NA 3.958750 0.014875000 10 NA
## 16 0.025000000 4.029412 0.005500000 10 173.94118
## 17 NA 3.127273 0.004333000 10 147.58333
## 18 NA NA NA 10 NA
## 19 NA NA NA 10 NA
## 20 NA 3.400000 0.002600000 10 168.60000
## 21 NA 2.083333 0.004333000 10 167.00000
## 22 NA NA NA 10 NA
## 23 NA NA NA 10 NA
## 24 NA 2.583333 0.005833000 10 161.33333
## 25 NA NA NA 10 NA
## 26 NA NA NA 10 NA
## 27 NA NA NA 10 NA
## 28 0.020000000 4.687500 0.013970000 10 156.50000
## 29 NA NA NA 10 NA
## 30 NA NA NA 10 NA
## 31 NA 3.000000 0.012181000 10 145.00000
## 32 NA 4.011111 0.011979000 10 NA
## 33 NA 3.125000 0.006625000 10 153.12500
## 34 0.023000000 5.500000 0.017083000 10 171.20000
## 35 NA NA NA 10 NA
## 36 NA NA NA 10 NA
## 37 NA 3.371429 0.015857000 10 NA
## 38 NA NA NA 10 NA
## 39 NA NA NA 10 NA
## 40 0.002500000 3.412500 0.017125000 10 NA
## 41 NA 2.680000 0.010590000 10 NA
## 42 NA 1.750000 0.003500000 10 156.00000
## 43 NA NA NA 10 NA
## 44 NA NA NA 10 NA
## 45 NA NA NA 10 NA
## 46 NA NA NA 10 NA
## 47 NA NA NA 10 NA
## 48 0.006000000 4.800000 0.016723000 10 NA
## 49 NA 2.611111 0.004625000 10 155.33333
## 50 NA NA NA 10 NA
## 51 0.002500000 3.063750 0.011000000 10 NA
## 52 NA NA NA 10 NA
## 53 0.006750000 4.282222 0.014250000 10 152.00000
## 54 0.137500000 3.928571 0.011571000 10 170.75000
## 55 NA NA NA 10 NA
## 56 0.020000000 4.833333 0.009727000 10 163.83333
## 57 NA 3.191111 0.010777000 10 159.00000
## 58 0.025000000 3.090909 0.013700000 10 167.28571
## 59 NA NA NA 10 NA
## 60 NA 2.500000 0.007500000 10 157.16667
## 61 0.002500000 3.440000 0.017800000 10 NA
## 62 NA NA NA 10 NA
## 63 0.002500000 2.900000 0.017444000 10 NA
## 64 0.025000000 3.777778 0.010625000 10 178.12500
## 65 NA NA NA 10 NA
## 66 0.004000000 3.150000 0.011035000 10 NA
## 67 NA NA NA 10 NA
## 68 NA NA NA 10 NA
## 69 NA NA NA 10 NA
## 70 NA 6.800000 0.009000000 70 NA
## 71 NA 3.092262 0.004250000 70 201.88690
## 72 NA 2.748413 0.004151000 70 197.38889
## 73 NA 3.450000 0.005200000 70 234.45454
## 74 NA 4.100000 0.008400000 70 216.20000
## 75 NA 3.303571 0.004035667 70 201.19048
## 76 NA 2.437500 0.003291500 70 209.00000
## 77 NA 4.160000 0.004000000 70 NA
## 78 NA 3.888889 0.005233333 70 205.83333
## 79 NA 4.200000 0.006200000 70 216.97778
## 80 NA 3.980000 0.004800000 70 NA
## 81 NA 5.828571 0.013000000 70 182.42857
## 82 NA 1.585000 0.003056000 70 170.85714
## 83 NA 3.594445 0.004177667 70 197.44444
## 84 NA 3.329365 0.003849000 70 199.32540
## 85 NA 1.850000 0.002812000 70 212.50000
## 86 NA 3.666667 0.007167000 70 218.50000
## 87 NA 4.341666 0.008783500 70 214.43333
## 88 NA 4.500000 0.006600000 70 218.20000
## 89 NA 2.916667 0.005833000 70 213.83333
## 90 NA 3.593636 0.003944000 70 209.44444
## 91 NA 7.781250 0.021280000 70 206.10714
## 92 NA 8.116667 0.010833000 70 NA
## 93 NA 3.615312 0.004358500 70 205.56801
## 94 NA 6.083333 0.013060000 70 187.00000
## 95 NA 5.475000 0.012500000 70 192.37500
## 96 NA 5.634524 0.012708333 70 187.68452
## 97 NA 4.422222 0.008911333 70 213.84444
## 98 NA 3.808333 0.008750000 70 192.43333
## 99 NA 2.585000 0.002025000 70 233.12500
## 100 NA 4.533333 0.006667000 70 NA
## 101 NA 3.812500 0.006250000 70 217.25000
## 102 NA 2.693651 0.004373333 70 196.62698
## 103 NA 4.316667 0.010167000 70 NA
## 104 NA 4.500000 0.008800000 70 210.80000
## 105 NA 3.857143 0.009654000 70 NA
## 106 NA 2.823333 0.003900000 70 219.08333
## 107 NA 3.916667 0.008500000 70 193.66667
## 108 NA 5.071429 0.008571000 70 205.71429
## 109 0.008500000 4.528571 0.011327000 70 NA
## 110 NA 5.250000 0.012476000 70 177.75000
## 111 NA 4.085714 0.006576000 70 100.00000
## 112 NA 3.366667 0.007016500 70 189.03333
## 113 NA 2.375000 0.003250000 70 204.00000
## 114 NA 2.380000 0.002923000 70 232.00000
## 115 NA 2.045000 0.003542000 70 240.00000
## 116 NA 4.273809 0.010131000 70 183.83333
## 117 NA 6.420000 0.003800000 70 NA
## 118 NA 3.958334 0.010083500 70 197.33333
## 119 NA NA NA 70 NA
## 120 NA 6.166667 0.036667000 70 203.83333
## 121 NA 3.909091 0.004909000 70 227.72727
## 122 NA 4.333333 0.006400000 70 218.24444
## 123 NA 3.575000 0.006816667 70 189.70000
## 124 NA 3.291667 0.004291667 70 202.29167
## 125 NA 2.960318 0.004264000 70 200.44246
## 126 NA 4.166667 0.007555333 70 217.22222
## 127 NA 1.830000 0.001944000 70 222.00000
## 128 NA 4.034863 0.004675000 70 207.79545
## 129 NA 3.600000 0.008500000 70 239.63636
## 130 NA 3.357143 0.007714000 70 216.28571
## 131 NA 5.407143 0.012214500 70 180.31250
## 132 NA 3.467460 0.003963333 70 198.46825
## 133 NA 1.300000 0.003160000 70 210.40000
## 134 NA 4.000000 0.005733333 70 212.77778
## 135 NA 3.440000 0.006334000 70 NA
## 136 NA 3.294643 0.003946333 70 200.88095
## 137 NA 3.928571 0.011042000 70 NA
## 138 NA 2.533333 NA 70 NA
## 139 NA 4.027762 0.005722500 70 207.80903
## 140 NA 4.966667 0.006448000 70 NA
## 141 NA 3.670000 0.004700000 70 205.82353
## 142 NA 3.844445 0.008666667 70 192.84444
## 143 NA 4.060750 0.006445500 70 205.62500
## 144 NA 3.755556 0.004633333 70 200.36667
## 145 NA 2.328462 0.002250000 70 224.08333
## 146 NA 2.500000 0.003166500 70 209.25000
## 147 NA 1.723333 0.004138000 70 184.66667
## 148 NA 4.500000 0.006600000 70 218.20000
## 149 NA 8.700000 0.002000000 70 NA
## 150 NA 4.833333 0.009333000 70 194.50000
## 151 NA 4.616667 0.007916500 70 203.02083
## 152 NA 5.752381 0.012875000 70 184.36905
## 153 NA 4.785714 0.012429000 70 210.85714
## 154 NA 2.500000 0.004050000 70 228.50000
## 155 NA 2.605000 0.003775000 70 226.50000
## 156 NA 4.379167 0.008641750 70 214.71667
## 157 NA 4.187500 0.005375000 70 224.75000
## 158 NA 4.050000 0.011167000 70 NA
## 159 NA 3.666667 0.006900000 70 235.50000
## 160 NA 3.512500 0.005725000 70 188.95000
## 161 NA 4.062500 0.007166500 70 217.25000
## 162 NA 7.000000 0.015599000 70 209.71429
## 163 NA 5.537500 0.012562500 70 190.31250
## 164 NA 3.216667 0.003133000 70 205.33333
## 165 NA 9.900000 0.028928000 70 190.80000
## 166 NA 2.951667 0.004725000 70 215.72727
## 167 NA 3.015873 0.004928667 70 200.62698
## 168 NA 3.625000 0.007667000 70 219.41667
## 169 NA 3.987500 0.006462000 70 207.00000
## 170 NA 5.752381 0.012666667 70 182.16071
## 171 NA 4.166667 0.005333000 70 NA
## 172 NA 4.000000 0.006933200 70 217.26667
## 173 NA NA NA 70 NA
## 174 NA 4.353333 0.008480000 70 215.24000
## 175 NA 4.036154 0.004675000 70 207.09091
## 176 NA 3.929412 0.005545000 70 206.56250
## 177 NA 1.368333 0.001117000 70 150.50000
## 178 NA 1.320000 0.000648000 70 145.80000
## 179 NA 1.800000 0.001120000 70 147.71429
## 180 NA 1.200000 0.003144000 70 NA
## 181 0.030000000 1.700000 0.001500000 70 134.42857
## 182 NA 1.281250 0.001750000 70 139.00000
## 183 NA NA 0.000520000 70 130.00000
## 184 NA 1.913333 0.001432000 70 NA
## 185 NA 2.000000 0.002125000 70 133.20000
## 186 NA 1.562857 0.001370000 70 156.85714
## 187 NA 1.380000 0.001387000 70 NA
## 188 0.030000000 1.708333 0.001833000 70 140.75000
## 189 0.025000000 1.590909 0.001364000 70 127.72727
## 190 NA 1.070000 0.001195000 70 153.16667
## 191 NA 1.203333 0.000940000 70 154.60000
## 192 NA NA 0.000540000 70 154.50000
## 193 NA 2.043403 0.001598000 70 131.50000
## 194 0.030000000 1.875000 0.001453000 70 139.75000
## 195 NA 1.000000 0.001415000 70 149.50000
## 196 NA NA 0.001230000 70 155.00000
## 197 0.024000000 1.562500 0.001591000 70 138.33333
## 198 NA 1.875000 NA 70 143.00000
## 199 NA 1.307692 0.002500000 70 143.16667
## 200 NA 1.833333 0.000807000 70 133.85714
## 201 NA 1.642857 0.001333000 70 133.66667
## 202 0.025000000 1.772727 0.001545000 70 137.18182
## 203 NA 1.448333 0.000985000 70 135.50000
## 204 0.030000000 1.666667 0.001583000 70 124.07500
## 205 NA 1.231667 0.000888000 70 NA
## 206 0.025000000 2.041667 0.001296000 70 141.11111
## 207 NA 1.445714 0.001333000 70 143.85714
## 208 NA 1.566667 0.001330000 70 NA
## 209 0.030000000 1.406250 0.001692000 70 132.06250
## 210 NA 1.010000 0.000685000 70 155.33333
## 211 0.025000000 1.416667 0.001332000 70 139.12500
## 212 NA 1.166667 0.001560000 70 157.28571
## 213 0.048400000 1.882500 0.001574000 70 140.60000
## 214 NA 1.255000 0.000783000 70 NA
## 215 NA NA 0.001010000 70 165.00000
## 216 NA NA NA 70 NA
## 217 0.005000000 1.860000 0.001058000 70 148.33333
## 218 NA NA NA 70 NA
## 219 NA 2.295455 0.000992000 70 110.80000
## 220 0.005000000 1.800000 0.001478000 70 136.00000
## 221 NA 2.650000 0.002000000 70 NA
## 222 NA NA NA 70 NA
## 223 NA 1.338333 0.000517000 70 142.83333
## 224 NA NA 0.000697000 70 137.33333
## 225 0.030000000 2.111111 0.001111000 70 118.22222
## 226 NA 2.031250 0.002062500 70 132.35000
## 227 NA 1.750000 0.002111000 70 141.00000
## 228 NA 1.617143 0.001550000 70 142.16667
## 229 NA 1.150000 0.000625000 70 165.00000
## 230 NA 2.050000 0.002667000 70 NA
## 231 0.030000000 1.500000 0.001222000 70 134.61111
## 232 NA 1.260000 0.001216000 70 162.14286
## 233 NA 1.642857 0.001154000 70 131.00000
## 234 NA 1.200000 0.000790000 70 NA
## 235 0.006000000 2.175000 0.001283000 70 134.60000
## 236 0.012250000 1.668182 0.001141000 70 145.00000
## 237 0.030000000 2.076923 0.001385000 70 134.66154
## 238 0.030000000 1.846154 0.002308000 70 134.23077
## 239 NA 1.000000 0.002414000 70 168.00000
## 240 0.005000000 2.023077 0.001407000 70 146.66667
## 241 NA 1.522000 0.000900000 70 146.50000
## 242 NA 1.818182 0.001364000 70 132.45454
## 243 NA 1.166667 0.001444000 70 137.04444
## 244 NA 1.227143 0.002580000 70 NA
## 245 NA 2.031250 0.001571000 70 131.50000
## 246 NA 2.512500 0.002000000 70 NA
## 247 0.030000000 2.166667 0.001500000 70 134.63333
## 248 NA 1.000000 0.001153000 70 142.66667
## 249 NA 2.050000 0.002667000 70 NA
## 250 0.030000000 1.642857 0.001143000 70 123.71429
## 251 NA 1.296703 0.002861000 70 142.29762
## 252 NA NA 0.000615000 70 143.00000
## 253 NA 1.916667 0.001636000 70 125.08333
## 254 NA 2.153935 0.001732000 70 131.50000
## 255 0.025000000 1.535714 0.001527000 70 129.90000
## 256 NA 1.200000 0.000898000 70 161.16667
## 257 0.025000000 1.650000 0.001900000 70 143.20000
## 258 NA 1.637500 0.000678000 70 141.00000
## 259 NA 1.722222 0.001444000 70 142.66667
## 260 NA NA NA 185 NA
## 261 NA NA NA 185 NA
## 262 0.009440000 1.693333 0.001860000 185 NA
## 263 NA NA NA 185 NA
## 264 0.004540000 1.123333 0.000752000 185 NA
## 265 NA NA NA 185 NA
## 266 NA NA NA 185 NA
## 267 NA 1.500000 0.001000000 185 44.00000
## 268 NA NA NA 185 NA
## 269 NA 2.000000 0.001000000 185 26.00000
## 270 NA NA NA 185 NA
## 271 NA NA NA 185 NA
## 272 0.022000000 1.562500 0.001075000 185 43.32500
## 273 NA 1.566667 0.001000000 185 98.66667
## 274 0.004000000 1.394286 0.000871000 185 84.22857
## 275 NA NA NA 185 NA
## 276 NA 2.083333 0.002000000 185 57.83333
## 277 0.012000000 NA 0.000802000 185 72.00000
## 278 NA NA NA 185 NA
## 279 NA 1.750000 0.001750000 185 72.25000
## 280 NA 1.400000 0.001200000 185 56.18000
## 281 0.012000000 1.000000 0.000697000 185 63.00000
## 282 NA NA NA 185 NA
## 283 NA NA NA 185 NA
## 284 0.004000000 1.448571 0.000461000 185 83.38333
## 285 NA 1.212000 0.000808000 185 62.98000
## 286 NA 1.800000 0.001000000 185 57.98000
## 287 NA NA NA 185 NA
## 288 0.022000000 1.598571 0.000814000 185 69.51429
## 289 0.021000000 1.583333 0.001000000 185 75.26667
## 290 NA NA NA 185 NA
## 291 NA NA NA 185 NA
## 292 0.012500000 1.006667 0.000513000 185 58.06667
## 293 NA 1.800000 0.001400000 185 54.60000
## 294 0.006210000 1.896667 0.000900000 185 75.80000
## 295 0.009000000 1.028571 0.001004000 185 NA
## 296 NA NA NA 185 NA
## 297 NA NA NA 185 NA
## 298 NA 1.416667 0.001167000 185 58.30000
## 299 NA 1.500000 0.001000000 185 56.66667
## 300 NA 1.250000 0.001000000 185 76.00000
## 301 0.004000000 1.480000 0.000860000 185 66.34000
## 302 NA 2.000000 0.001333000 185 82.56667
## 303 NA NA NA 185 NA
## 304 NA NA NA 185 NA
## 305 0.013000000 1.393333 0.000775000 185 86.75000
## 306 NA NA NA 185 NA
## 307 NA NA NA 185 NA
## 308 0.004000000 1.172500 0.000961000 185 NA
## 309 NA 1.333333 0.001000000 185 85.65000
## 310 NA 1.666667 0.001000000 185 58.33333
## 311 NA 4.982143 0.014179000 75 170.53571
## 312 NA 6.000000 0.016686000 75 178.60870
## 313 NA 3.900000 0.005200000 75 154.58000
## 314 0.030000000 3.586207 0.005138000 75 181.58621
## 315 NA 3.166667 0.003400000 75 164.83333
## 316 1.654000000 3.274286 0.002491000 75 158.40000
## 317 NA 3.240000 0.006760000 75 160.46000
## 318 0.845000000 3.571667 0.003333000 75 147.21667
## 319 5.200000000 3.250000 0.007348000 75 188.13636
## 320 NA 2.800000 0.002365000 75 NA
## 321 1.569000000 4.481667 0.001883000 75 180.66667
## 322 0.077850000 NA NA 75 NA
## 323 3.890000000 8.260000 0.007332000 75 165.50000
## 324 NA NA NA 75 NA
## 325 NA 5.884615 0.020240000 75 196.00000
## 326 NA 2.602000 0.001482000 75 198.20000
## 327 1.565000000 3.031667 0.004680000 75 187.33333
## 328 NA 6.634783 0.020348000 75 171.21053
## 329 NA 7.893548 0.018032000 75 152.41667
## 330 NA 3.300000 0.003200000 75 173.80000
## 331 NA 6.878750 0.011110000 75 165.95238
## 332 NA 8.828571 0.009815000 75 142.03571
## 333 NA 9.444444 0.015087000 75 154.96296
## 334 NA 2.485714 0.006107000 75 210.71429
## 335 NA 3.562000 0.001620000 75 159.00000
## 336 1.599500000 4.575714 0.005633000 75 175.42857
## 337 NA 6.157895 0.013400000 75 163.57143
## 338 NA 4.971429 0.005696000 75 183.42857
## 339 NA 2.085714 0.003344000 75 NA
## 340 NA 6.010714 0.008418000 75 179.00000
## 341 NA NA NA 75 NA
## 342 1.599000000 2.525000 0.002283000 75 169.66667
## 343 0.015600000 8.851667 0.005128000 75 144.50000
## 344 1.599000000 5.363333 0.001450000 75 169.16667
## 345 NA 6.016129 0.016452000 75 186.90323
## 346 0.100000000 5.070000 0.002738000 75 NA
## 347 NA 4.000000 0.005000000 75 166.00000
## 348 NA 7.565217 0.025000000 75 180.08696
## 349 0.059500000 3.021667 0.003552000 75 NA
## 350 NA 2.166667 0.002622000 75 NA
## 351 NA 2.466667 0.003353000 75 174.00000
## 352 0.084150000 NA NA 75 NA
## 353 NA 3.166667 0.004286000 75 167.85714
## 354 NA 6.064356 0.011245000 75 167.80000
## 355 0.014750000 2.246667 0.002660000 75 202.33333
## 356 1.740000000 6.471429 0.006399000 75 170.42857
## 357 0.835500000 3.381429 0.002940000 75 NA
## 358 NA 4.500000 0.004667000 75 153.50000
## 359 NA 7.586364 0.021572000 75 160.52632
## 360 NA 3.200000 0.006713000 75 199.16667
## 361 NA 7.957895 0.026762000 75 178.15789
## 362 NA 5.153846 0.012440000 75 176.34615
## 363 NA 6.046741 0.011231500 75 167.80000
## 364 NA 5.880952 0.010024000 75 142.22727
## 365 0.762800000 2.561667 0.002010000 75 NA
## 366 NA 6.464000 0.023236000 75 168.57368
## 367 NA 4.288462 0.007509000 75 154.53333
## 368 NA NA NA 75 NA
## 369 NA 2.683333 0.004097000 75 NA
## 370 NA 6.973684 0.018592000 75 183.94444
## 371 NA NA 0.001643000 145 67.33333
## 372 NA NA 0.000653000 145 61.00000
## 373 NA 7.850000 0.004300000 145 73.50000
## 374 NA 1.583333 0.001000000 145 NA
## 375 NA NA 0.001133000 145 NA
## 376 NA 1.863636 0.001091000 145 51.55000
## 377 NA 2.622222 0.000794000 145 NA
## 378 NA NA NA 145 NA
## 379 NA 2.333333 0.001333000 145 53.66667
## 380 NA NA 0.000892000 145 60.20000
## 381 NA 2.438333 0.000445000 145 NA
## 382 NA NA 0.000497000 145 57.20000
## 383 NA 4.378571 0.003286000 145 NA
## 384 NA 1.800000 0.001000000 145 39.00000
## 385 NA 2.333333 0.001707000 145 51.00000
## 386 NA 1.958333 0.002500000 145 NA
## 387 NA 1.928571 0.001000000 145 63.98333
## 388 NA NA 0.001695000 145 67.16667
## 389 NA NA 0.001017000 145 59.42857
## 390 NA NA 0.001200000 145 NA
## 391 0.182500000 9.111111 0.004778000 145 71.22222
## 392 NA 2.166667 0.001667000 145 56.33333
## 393 NA 2.500000 0.001286000 145 51.42857
## 394 NA 1.817143 0.001483000 145 67.78333
## 395 NA 1.500000 0.001000000 145 NA
## 396 NA 2.500000 0.001000000 145 49.66667
## 397 NA NA 0.000950000 145 61.00000
## 398 NA 2.585714 0.001383000 145 NA
## 399 NA 17.055556 0.001286000 145 66.55556
## 400 NA 2.187500 0.003500000 145 NA
## 401 NA NA 0.000523000 145 59.50000
## 402 NA 2.380952 0.001549000 145 51.71429
## 403 NA 2.166667 0.004000000 145 NA
## 404 NA 1.706154 0.000503000 145 NA
## 405 NA 1.736667 0.001697000 145 NA
## 406 NA 2.183333 0.000719000 145 NA
## 407 NA 2.389286 0.001643000 145 57.10000
## 408 NA 4.700000 0.002000000 145 56.20000
## 409 NA 2.470909 0.001925000 145 53.22500
## 410 NA 1.815714 0.000557000 145 57.14286
## 411 NA 1.700000 0.001000000 145 48.40000
## 412 NA 1.783636 0.002350000 145 56.53333
## 413 NA NA 0.000975000 145 NA
## 414 NA 1.602500 0.000941000 145 64.25714
## 415 NA NA 0.001670000 145 68.16667
## 416 NA 1.600000 0.002800000 145 NA
## 417 NA 1.800000 0.001724000 145 50.00000
## 418 NA 1.612857 0.000943000 145 60.00000
## 419 NA 1.772727 0.001091000 145 58.06667
## 420 NA 3.200000 0.001262000 145 53.25000
## 421 NA NA 0.001375000 145 95.50000
## 422 NA 1.565000 0.000313000 145 NA
## 423 NA NA 0.000857000 145 NA
## 424 NA NA 0.000733000 145 61.00000
## 425 NA 1.837500 0.002391000 145 58.45000
## 426 NA 2.250000 0.001500000 145 NA
## 427 NA NA NA 145 NA
## 428 NA NA 0.001236000 145 63.28571
## 429 NA NA 0.002028000 145 70.40000
## 430 NA 2.127692 0.000720000 145 60.95000
## 431 NA 1.733333 0.000638000 145 61.00000
## 432 NA 2.166667 0.001000000 145 53.23333
## 433 NA 3.142857 0.001765000 145 59.00000
## 434 NA 2.100000 0.001350000 145 62.00000
## 435 NA 2.562500 0.003000000 145 NA
## 436 NA NA 0.000412000 145 58.60000
## 437 NA NA 0.000906000 145 58.42857
## 438 NA 2.451667 0.001623000 145 68.86667
## 439 NA 1.833333 0.001000000 145 51.60000
## 440 NA NA 0.002506000 145 NA
## 441 NA 3.333333 0.001250000 145 65.85000
## 442 NA 1.071429 0.001000000 35 NA
## 443 NA NA NA 35 NA
## 444 NA NA NA 35 NA
## 445 NA 1.060000 0.000412000 35 121.16667
## 446 NA NA NA 35 NA
## 447 NA 1.166667 0.000507000 35 NA
## 448 NA 1.078571 0.000519000 35 204.85714
## 449 NA NA NA 35 NA
## 450 NA NA 0.000387000 35 117.33333
## 451 NA 1.357143 0.001000000 35 101.01429
## 452 NA NA 0.000542000 35 131.80000
## 453 NA NA NA 35 NA
## 454 NA 1.000000 0.000637000 35 NA
## 455 NA NA NA 35 NA
## 456 NA 1.416667 0.001000000 35 133.53333
## 457 NA NA 0.000424000 35 116.57143
## 458 NA 1.050000 0.001000000 35 189.14286
## 459 NA 1.333333 0.001000000 35 NA
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## 1785 0.041000000 1.500000 0.001343000 66 147.14286
## 1786 0.063500000 NA 0.000719000 66 165.16667
## 1787 0.062000000 NA 0.001062000 66 166.66667
## 1788 NA 1.800000 0.002717000 66 133.00000
## 1789 NA NA 0.001715000 66 167.00000
## 1790 NA 2.350000 0.002000000 66 NA
## 1791 0.170000000 1.590000 0.001217000 66 149.83333
## 1792 NA NA 0.001880000 66 NA
## 1793 0.035000000 1.557500 0.000385000 66 125.25000
## 1794 NA 2.416667 0.003000000 66 149.66667
## 1795 0.041000000 1.588333 0.001333000 66 147.00000
## 1796 NA NA 0.002357000 66 164.00000
## 1797 NA 1.666667 0.001667000 66 147.66667
## 1798 NA 1.916667 0.001600000 66 142.00000
## 1799 0.170000000 1.922000 0.001240000 66 147.40000
## 1800 NA NA 0.001212000 66 152.00000
## 1801 NA NA 0.001460000 66 164.50000
## 1802 NA 2.165000 0.001100000 66 148.50000
## 1803 NA 1.625000 0.001250000 66 136.75000
## 1804 NA NA 0.001656000 66 140.50000
## 1805 NA NA 0.000680000 66 NA
## 1806 NA NA 0.000546000 66 NA
## 1807 NA 3.833333 0.002833000 66 143.66667
## 1808 NA NA 0.001115000 66 160.50000
## 1809 0.043250000 1.240000 0.000713000 66 NA
## 1810 NA 2.800000 0.001000000 66 NA
## 1811 NA 2.583333 0.003038000 66 140.00000
## 1812 NA 1.416667 0.001333000 66 145.83333
## 1813 NA NA NA 66 NA
## 1814 NA 2.192857 0.002030000 66 NA
## 1815 NA 1.666667 0.001667000 66 139.21667
## 1816 NA 2.100000 0.001200000 66 137.00000
## 1817 NA NA 0.000638000 66 NA
## 1818 NA 2.500000 0.001436000 66 127.40000
## 1819 NA NA 0.005816000 66 158.00000
## 1820 NA 3.800000 0.001600000 66 NA
## 1821 0.040750000 2.087143 0.001500000 66 139.85714
## 1822 NA NA 0.001642000 66 160.00000
## 1823 NA 2.700000 0.001440000 66 122.80000
## 1824 NA 1.785714 0.002825000 66 129.00000
## 1825 NA NA 0.000635000 66 159.00000
## 1826 NA 3.916667 0.013167000 66 NA
## 1827 0.056000000 1.321667 0.000612000 66 NA
## 1828 0.044500000 1.865000 0.000915000 66 NA
## 1829 NA 1.600000 0.000805000 66 NA
## 1830 NA 4.216667 0.001667000 66 NA
## 1831 NA 2.416667 0.002000000 66 121.83333
## 1832 NA 1.584286 0.000726000 66 151.14286
## 1833 NA NA 0.000733000 66 153.66667
## 1834 NA 3.216667 0.001500000 66 NA
## 1835 NA 2.971429 0.003487000 66 140.00000
## 1836 NA 1.916667 0.001833000 66 130.71667
## 1837 NA 1.600000 0.001500000 66 143.83333
## 1838 0.085500000 NA 0.001223000 66 158.00000
## 1839 NA 1.700000 0.001400000 66 143.20000
## 1840 NA NA 0.001495000 66 166.50000
## 1841 NA NA NA 66 NA
## 1842 0.040500000 1.726250 0.000324000 66 138.20000
## 1843 0.072290000 NA 0.001641000 66 NA
## 1844 NA 2.250000 0.001842000 66 131.66667
## 1845 NA 1.583333 0.001000000 66 139.83333
## 1846 0.041000000 1.308571 0.000770000 66 150.14286
## 1847 NA 3.000000 0.002667000 66 142.16667
## 1848 NA 3.083333 0.002000000 66 129.83333
## 1849 NA 1.725000 0.001732000 66 NA
## 1850 NA 1.500000 0.001318000 66 146.16667
## 1851 NA 1.806667 0.001657000 20 247.00000
## 1852 NA 3.821667 0.000940000 20 176.50000
## 1853 NA 3.101667 0.004417000 20 207.00000
## 1854 NA 5.071000 0.018600000 20 NA
## 1855 NA 2.833333 0.002500000 20 189.50000
## 1856 NA 4.000000 0.001500000 20 177.00000
## 1857 NA 2.785714 0.001571000 20 194.00000
## 1858 NA 3.515000 0.007667000 20 NA
## 1859 NA 3.421429 0.010406000 20 NA
## 1860 NA 3.833333 0.001833000 20 199.00000
## 1861 NA 2.875000 0.001750000 20 173.00000
## 1862 NA 1.890000 0.001352000 20 200.83333
## 1863 NA 3.200000 0.005163000 20 194.60000
## 1864 NA 4.100000 0.003608000 20 197.80000
## 1865 NA 3.196000 0.000960000 20 199.80000
## 1866 NA 5.500000 0.000800000 20 164.00000
## 1867 NA 3.650000 0.012500000 20 NA
## 1868 NA 3.916667 0.003000000 20 212.83333
## 1869 NA 4.442857 0.004429000 20 NA
## 1870 NA NA 0.000805000 20 177.00000
## 1871 NA 2.121667 0.001690000 20 NA
## 1872 NA 4.285714 0.003286000 20 188.14286
## 1873 NA 2.333333 0.003500000 20 192.66667
## 1874 0.220000000 3.000000 0.002750000 20 199.20000
## 1875 NA 3.311667 0.001450000 20 199.66667
## 1876 NA 1.000000 0.001666000 20 176.60000
## 1877 NA 2.820000 0.001116000 20 219.00000
## 1878 NA 3.571429 0.003811000 20 187.42857
## 1879 NA 1.930000 0.002094000 20 172.00000
## 1880 NA 3.083333 0.002833000 20 206.66667
## 1881 NA 1.470000 0.001566000 20 252.00000
## 1882 0.200000000 3.200000 0.006200000 20 204.20000
## 1883 NA 3.336000 0.001500000 20 195.40000
## 1884 NA 2.333333 0.001227000 20 NA
## 1885 NA 3.581250 0.007000000 20 NA
## 1886 NA 3.571429 0.004000000 20 217.71429
## 1887 0.190000000 3.416667 0.002400000 20 188.00000
## 1888 NA 3.616667 0.005039000 20 NA
## 1889 NA 3.083333 0.003500000 20 190.66667
## 1890 NA 2.170000 0.001053000 20 NA
## 1891 NA 5.151667 0.011682000 20 NA
## 1892 NA 2.050000 0.001512000 20 218.33333
## 1893 NA 2.950000 0.005077000 20 NA
## 1894 NA 3.013333 0.001762000 20 NA
## 1895 NA 3.500000 0.003500000 20 190.83333
## 1896 NA 3.226667 0.001693000 20 184.50000
## 1897 NA 2.880000 0.011800000 20 NA
## 1898 NA 1.566667 0.000897000 20 221.66667
## 1899 NA 3.416667 0.004458000 20 172.66667
## 1900 NA 3.666667 0.006617000 20 187.75000
## 1901 NA 2.525000 0.001075000 20 NA
## 1902 NA NA 0.000860000 20 221.00000
## 1903 NA 2.831667 0.002370000 20 186.16667
## 1904 NA 3.666667 0.005168000 20 190.83333
## 1905 NA 1.866667 0.001942000 20 192.33333
## 1906 NA 1.700000 0.000510000 130 NA
## 1907 NA 2.100000 0.001200000 130 75.70000
## 1908 NA 1.574286 0.001071000 130 99.35714
## 1909 NA 1.504000 0.000587000 130 NA
## 1910 NA 2.550000 0.002500000 130 NA
## 1911 NA 2.750000 0.001000000 130 84.50000
## 1912 NA 2.000000 0.001400000 130 NA
## 1913 NA 1.791667 0.001333000 130 NA
## 1914 NA 1.775000 0.000417000 130 70.50000
## 1915 NA 2.000000 0.001000000 130 NA
## 1916 NA 1.316667 0.000688000 130 113.16667
## 1917 NA 1.583333 0.000302000 130 49.00000
## 1918 0.014000000 1.370000 0.000637000 130 76.50000
## 1919 NA 1.666667 0.001000000 130 63.83333
## 1920 NA NA NA 130 NA
## 1921 NA 1.250000 0.000303000 130 92.75000
## 1922 NA 1.200000 0.000378000 130 69.20000
## 1923 NA 1.500000 0.001143000 130 106.35714
## 1924 NA 1.400000 0.001143000 130 100.42857
## 1925 NA 1.750000 0.001000000 130 93.16000
## 1926 NA NA NA 130 NA
## 1927 NA 2.000000 0.000510000 130 76.66667
## 1928 NA NA NA 130 NA
## 1929 NA 1.785714 0.001000000 130 74.71429
## 1930 NA 2.400000 0.001250000 130 71.84000
## 1931 NA 1.740000 0.000275000 130 NA
## 1932 NA 1.455000 0.000600000 130 87.51667
## 1933 NA 1.400000 0.001040000 130 101.00000
## 1934 NA 1.600000 0.000800000 130 90.80000
## 1935 NA 2.526667 0.001322000 130 NA
## 1936 NA 2.142857 0.003333000 130 NA
## 1937 NA 1.600000 0.001917000 130 NA
## 1938 NA 1.900000 0.001000000 130 78.80000
## 1939 NA 1.700000 0.001600000 130 75.20000
## 1940 NA 2.000000 0.001000000 130 96.25000
## 1941 NA 1.614286 0.001167000 130 90.51429
## 1942 NA 3.250000 0.001167000 130 57.66667
## 1943 NA 1.750000 0.001500000 130 87.83333
## 1944 NA 2.347143 0.000833000 130 61.87143
## 1945 NA NA NA 130 NA
## 1946 NA NA NA 130 NA
## 1947 NA 1.500000 0.001348000 130 113.00000
## 1948 NA 1.281667 0.000822000 130 98.35556
## 1949 NA 1.800000 0.001000000 130 58.20000
## 1950 0.104000000 1.000000 0.001236000 130 NA
## 1951 NA NA NA 130 NA
## 1952 NA 1.837143 0.000940000 130 107.30000
## 1953 NA 3.571429 0.001143000 130 63.14286
## 1954 NA 1.666667 0.001000000 130 NA
## 1955 NA 1.875000 0.001000000 130 NA
## 1956 0.014000000 NA NA 130 NA
## 1957 NA 2.121429 0.001306000 130 NA
## 1958 NA 1.906667 0.000790000 130 93.33333
## 1959 NA 1.511667 0.000680000 130 95.15000
## 1960 NA 1.487143 0.000933000 50 NA
## 1961 NA 1.376667 0.000385000 50 272.00000
## 1962 NA 1.388889 0.001000000 50 274.55556
## 1963 NA 1.582857 0.000583000 50 277.42857
## 1964 NA 1.881429 0.001460000 50 NA
## 1965 NA 2.285714 0.002833000 50 260.50000
## 1966 NA 1.918571 0.000917000 50 NA
## 1967 NA 1.601667 0.000733000 50 265.28571
## 1968 NA 1.110000 0.000976000 50 340.25000
## 1969 NA 1.875000 0.001333000 50 271.87500
## 1970 0.014000000 NA 0.000952000 50 295.00000
## 1971 NA 1.875000 0.002750000 50 263.00000
## 1972 NA NA 0.000634000 50 292.57143
## 1973 NA 2.050000 0.001500000 50 NA
## 1974 NA 1.350000 0.000604000 50 288.60000
## 1975 0.014000000 NA 0.000953000 50 300.50000
## 1976 NA 1.075000 0.002760000 50 284.80000
## 1977 NA 2.400000 0.001674000 50 266.00000
## 1978 NA 1.714286 0.002714000 50 280.85714
## 1979 NA 1.833333 0.001667000 50 259.66667
## 1980 NA 2.300000 0.002714000 50 267.20000
## 1981 NA 1.953333 0.003000000 50 NA
## 1982 NA 1.766667 0.002037000 50 NA
## 1983 NA 2.353333 0.002167000 50 NA
## 1984 NA 1.880000 0.001400000 50 245.20000
## 1985 NA 1.148333 0.001333000 50 NA
## 1986 NA NA NA 50 NA
## 1987 NA 2.158571 0.001330000 50 NA
## 1988 NA NA 0.001132000 50 285.50000
## 1989 NA 1.875000 0.002750000 50 262.00000
## 1990 NA 1.746667 0.001240000 50 271.16667
## 1991 NA 1.200000 0.001122000 50 NA
## 1992 NA 1.986000 0.000348000 50 277.80000
## 1993 NA 1.916667 0.001660000 50 260.83333
## 1994 NA 2.000000 0.003000000 50 259.00000
## 1995 NA NA 0.000810000 50 274.66667
## 1996 NA NA 0.000610000 50 302.00000
## 1997 NA 1.948000 0.000980000 50 273.40000
## 1998 NA NA 0.001385000 50 290.16667
## 1999 NA 1.536667 0.000958000 50 273.33333
## 2000 NA 1.083333 0.001167000 50 243.33333
## 2001 NA 2.795000 0.001388000 50 NA
## 2002 NA 1.600000 0.003800000 50 NA
## 2003 NA 1.875000 0.001250000 50 277.25000
## 2004 NA 1.666667 0.001000000 50 255.16667
## 2005 NA 1.500000 0.001547000 50 237.16667
## 2006 NA 1.165000 0.001105000 50 NA
## 2007 NA 1.714286 0.001286000 50 270.57143
## 2008 NA NA 0.000747000 50 289.00000
## 2009 NA 2.520000 0.002800000 50 NA
## 2010 NA 2.214286 0.001797000 50 265.42857
## 2011 NA 1.866667 0.002368000 50 NA
## 2012 NA 1.583333 0.001000000 50 256.80000
## 2013 NA 2.026000 0.001302000 50 260.80000
## 2014 NA 1.750000 0.001667000 50 267.33333
## 2015 NA 1.500000 0.001333000 50 249.50000
## 2016 NA 1.621429 0.000757000 50 263.57143
## 2017 0.014000000 NA NA 50 NA
## 2018 NA 2.911250 0.001485000 50 271.75000
## 2019 NA 1.875000 0.000948000 50 186.80000
## 2020 0.016510000 1.511667 0.000693000 50 199.66667
## 2021 NA 1.000000 0.000884000 50 216.80000
## 2022 NA 2.700000 0.001707000 50 230.84286
## 2023 NA 2.783333 0.001909000 50 197.66667
## 2024 NA 1.750000 0.001333000 50 184.66667
## 2025 NA 2.066667 0.002037000 50 NA
## 2026 NA 2.000000 0.001874000 50 196.00000
## 2027 NA 2.118182 0.001273000 50 201.91667
## 2028 NA 1.448333 0.000937000 50 239.16667
## 2029 NA 1.850000 0.004102000 50 227.50000
## 2030 0.004000000 3.007692 0.003199000 50 204.66667
## 2031 NA 1.683333 0.001267000 50 206.00000
## 2032 NA 1.500000 0.001167000 50 202.16667
## 2033 0.609200000 1.504286 0.000957000 50 195.57143
## 2034 NA 1.714286 0.001672000 50 194.37500
## 2035 NA 2.583333 0.002143000 50 185.00000
## 2036 NA 1.780000 0.012820000 50 204.16667
## 2037 NA 2.375000 0.001375000 50 192.00000
## 2038 NA 2.500000 0.001444000 50 156.80000
## 2039 NA 2.833333 0.002300000 50 197.83333
## 2040 NA 2.930769 0.002455000 50 174.16667
## 2041 NA 1.500000 0.001500000 50 192.16667
## 2042 NA 1.433333 0.001049000 50 NA
## 2043 NA 1.133333 0.000762000 50 NA
## 2044 NA 2.126667 0.002271000 50 227.28571
## 2045 NA 2.375000 0.001375000 50 192.00000
## 2046 NA 2.336667 0.003687000 50 NA
## 2047 NA 2.564286 0.006500000 50 191.00000
## 2048 NA 2.763636 0.002111000 50 171.00000
## 2049 NA 1.785714 0.002263000 50 200.71429
## 2050 NA 1.150000 0.000928000 50 NA
## 2051 NA 1.000000 0.000914000 50 201.00000
## 2052 NA 2.400000 0.003111000 50 199.80000
## 2053 NA 2.658889 0.002858000 50 207.50000
## 2054 NA 1.400000 0.001414000 50 241.00000
## 2055 NA 2.083333 0.001636000 50 186.66667
## 2056 NA 2.441176 0.002069000 50 193.60000
## 2057 NA 1.728571 0.000857000 50 207.57143
## 2058 NA 1.551667 0.001447000 50 205.75000
## 2059 NA 1.153333 0.000920000 50 205.00000
## 2060 NA 2.041667 0.001250000 50 196.23077
## 2061 NA 1.405714 0.000884000 50 NA
## 2062 NA 1.400000 0.002000000 50 187.75000
## 2063 NA 1.430000 0.000686000 50 192.75000
## 2064 NA 1.733333 0.000821000 50 199.28571
## 2065 NA 2.100000 0.001400000 50 179.00000
## 2066 NA 1.560000 0.000435000 50 217.00000
## 2067 NA 1.785714 0.001429000 50 203.57143
## 2068 NA 2.421667 0.003583000 50 NA
## 2069 NA 1.657143 0.001314000 50 184.28571
## 2070 NA 1.300000 0.000440000 50 NA
## 2071 NA 1.750000 0.001500000 50 185.33333
## 2072 NA 2.045455 0.001400000 50 200.81818
## 2073 NA 1.143333 0.000850000 50 237.50000
## 2074 NA 2.062500 0.002177000 50 197.14286
## 2075 NA 2.409091 0.001600000 50 191.72727
## 2076 NA 2.208333 0.003000000 50 207.33333
## 2077 0.020000000 2.166667 0.001676000 55 127.44444
## 2078 NA 2.166667 0.001500000 55 93.66667
## 2079 NA 1.541667 0.002800000 55 NA
## 2080 NA 1.750000 0.001500000 55 113.66667
## 2081 NA 1.954545 0.001468000 55 136.09091
## 2082 NA 2.083333 0.001000000 55 89.00000
## 2083 0.020000000 2.166667 0.001676000 55 127.44444
## 2084 NA 2.625000 0.003167000 55 NA
## 2085 0.239000000 1.733333 0.002222000 55 100.83333
## 2086 NA 2.250000 0.001805000 55 96.50000
## 2087 NA 2.333333 0.001500000 55 85.16667
## 2088 NA 1.712000 0.001147000 55 NA
## 2089 NA 2.678571 0.003333000 55 NA
## 2090 NA 2.656250 0.001485000 55 NA
## 2091 NA 2.500000 0.002167000 55 107.85714
## 2092 NA 2.214286 0.001429000 55 105.52857
## 2093 NA NA 0.001060000 55 105.50000
## 2094 NA NA NA 55 NA
## 2095 NA 2.166667 0.001667000 55 115.16667
## 2096 NA NA 0.000580000 55 135.00000
## 2097 NA 2.366667 0.000665000 55 108.50000
## 2098 NA 2.916667 0.001800000 55 93.83333
## 2099 NA NA 0.000700000 55 126.00000
## 2100 NA NA 0.000775000 55 134.50000
## 2101 NA NA 0.000593000 55 87.66667
## 2102 NA 2.200000 0.001600000 55 114.40000
## 2103 NA 1.785714 0.001571000 55 124.04286
## 2104 NA 2.750000 0.001833000 55 101.00000
## 2105 NA 2.250000 0.002380000 55 129.37500
## 2106 NA 2.703571 0.002869000 55 NA
## 2107 NA 3.714286 0.001714000 55 90.57143
## 2108 NA NA 0.000390000 55 109.00000
## 2109 NA 2.475000 0.004450000 55 NA
## 2110 NA 2.625000 0.001143000 55 71.75000
## 2111 NA 1.625000 0.003000000 55 NA
## 2112 NA 4.571429 0.001429000 55 113.31429
## 2113 NA 1.897143 0.001157000 55 NA
## 2114 0.200000000 1.600000 0.000730000 55 73.75000
## 2115 NA 1.900000 0.002000000 55 142.66667
## 2116 NA NA 0.000730000 55 96.00000
## 2117 NA 2.885000 0.001792000 55 NA
## 2118 NA 2.500000 0.004500000 55 NA
## 2119 NA 1.766667 0.002222000 55 119.55556
## 2120 NA 2.725000 0.001716500 55 106.30000
## 2121 NA 3.900000 0.002000000 55 92.40000
## 2122 NA 2.166667 0.001833000 55 104.36667
## 2123 NA 2.000000 0.000600000 55 102.00000
## 2124 NA 2.405556 0.002789000 55 NA
## 2125 NA NA NA 55 NA
## 2126 NA 1.600000 0.001078000 55 117.83333
## 2127 0.244000000 2.911667 0.001507000 5 184.83333
## 2128 0.049755000 NA 0.001637000 5 205.00000
## 2129 0.059500000 1.348333 0.001428000 5 178.50000
## 2130 0.025000000 1.990000 0.002225000 5 202.50000
## 2131 0.171500000 2.214286 0.003571000 5 199.28571
## 2132 0.025000000 3.398400 0.006280000 5 182.23077
## 2133 0.132000000 2.233333 0.004467000 5 185.65217
## 2134 0.025000000 4.500000 0.002250000 5 163.61539
## 2135 0.009500000 3.629630 0.007074000 5 184.40000
## 2136 NA 3.075000 0.007949000 5 177.50000
## 2137 0.106666667 4.115385 0.003080000 5 191.72727
## 2138 0.155000000 2.714286 0.002357000 5 168.23077
## 2139 NA NA 0.002533000 5 178.00000
## 2140 NA NA NA 5 NA
## 2141 0.063000000 1.440000 0.000988000 5 193.00000
## 2142 0.099950000 1.663333 0.001213000 5 211.80000
## 2143 0.206000000 2.013043 0.002565000 5 185.25000
## 2144 0.094000000 2.840000 0.004517000 5 177.73077
## 2145 0.225000000 3.931818 0.003037000 5 183.81818
## 2146 0.385000000 2.950000 0.001286000 5 196.40000
## 2147 0.215000000 2.750000 0.001400000 5 174.50000
## 2148 0.005000000 1.525000 0.002500000 5 183.75000
## 2149 0.031666667 3.684211 0.002579000 5 203.26667
## 2150 0.005000000 3.400000 0.004706000 5 184.72727
## 2151 0.067250000 NA 0.000836000 5 190.00000
## 2152 0.153500000 2.145714 0.002689000 5 NA
## 2153 NA 1.566667 0.000943000 5 219.00000
## 2154 0.385000000 2.886364 0.003905000 5 171.40909
## 2155 0.286200000 2.346154 0.003769000 5 189.00000
## 2156 0.307500000 2.466667 0.002111000 5 189.80000
## 2157 0.218866667 2.645000 0.000800000 5 203.00000
## 2158 0.054000000 1.950000 0.001303000 5 192.00000
## 2159 0.347000000 NA 0.001124000 5 185.33333
## 2160 0.183250000 3.373750 0.001418000 5 199.62500
## 2161 0.054000000 2.028571 0.001053000 5 214.85714
## 2162 0.062500000 1.650000 0.001107000 5 183.16667
## 2163 0.020500000 3.819500 0.007350000 5 186.00000
## 2164 0.097750000 3.224138 0.002206000 5 174.13793
## 2165 0.062500000 1.533333 0.001147000 5 200.00000
## 2166 0.031666667 2.163158 0.003158000 5 196.62500
## 2167 0.106450000 1.572000 0.001592000 5 222.00000
## 2168 0.180000000 2.800000 0.001636000 5 190.72727
## 2169 0.385000000 2.851667 0.001600000 5 192.16667
## 2170 0.105875000 1.700000 0.002168000 5 206.00000
## 2171 0.007875000 2.687586 0.005241000 5 174.81818
## 2172 0.072333333 3.020833 0.003273000 5 207.11765
## 2173 0.238571429 2.461538 0.002000000 5 175.15385
## 2174 0.003500000 2.923077 0.004091000 5 183.00000
## 2175 0.004000000 4.476333 0.008168000 5 185.00000
## 2176 0.062500000 1.600000 0.001093000 5 200.83333
## 2177 0.046142857 2.687500 0.003708000 5 183.22222
## 2178 0.153500000 2.660000 0.002957000 5 NA
## 2179 0.011000000 3.321154 0.006530000 5 192.75000
## 2180 NA NA 0.000880000 5 NA
## 2181 0.014666667 2.760417 0.003543000 5 185.30769
## 2182 0.150000000 2.930000 0.001166000 5 NA
## 2183 0.180000000 2.857143 0.003000000 5 174.57143
## 2184 NA NA 0.001947000 5 201.50000
## 2185 NA 2.806667 0.000905000 5 188.66667
## 2186 0.002500000 2.570588 0.006313000 5 180.80000
## 2187 0.051000000 2.300000 0.001203000 5 NA
## 2188 0.054000000 1.983333 0.002233000 5 182.16667
## 2189 0.050000000 2.148148 0.003845000 5 165.70370
## 2190 0.038000000 2.934783 0.005993000 5 184.35000
## 2191 0.153500000 2.247143 0.001244000 5 NA
## 2192 0.054000000 1.916667 0.002608000 5 193.33333
## 2193 0.059500000 NA 0.001440000 5 195.00000
## 2194 0.190500000 4.250000 0.003857000 5 177.00000
## 2195 0.030000000 2.940000 0.006059000 5 185.42857
## 2196 0.002380000 NA 0.001285000 5 194.50000
## 2197 0.050500000 3.295455 0.004244000 5 180.95454
## 2198 0.054500000 1.783333 0.000822000 5 195.16667
## 2199 0.236500000 1.944000 0.002033000 5 192.16667
## 2200 0.066250000 1.976667 0.003283000 70 169.33333
## 2201 0.060625000 3.593333 0.005800000 70 126.13333
## 2202 NA 6.454545 0.015444000 70 234.00000
## 2203 NA 6.568182 0.023000000 70 234.00000
## 2204 0.030000000 2.375000 0.010250000 70 251.58333
## 2205 NA 3.750000 0.014000000 70 NA
## 2206 NA 3.931818 0.015600000 70 216.00000
## 2207 0.034400000 NA 0.002570000 70 217.50000
## 2208 NA 3.937500 0.014166667 70 NA
## 2209 0.034410000 NA NA 70 NA
## 2210 0.005000000 3.893750 0.010185000 70 235.90000
## 2211 0.026000000 1.976000 0.001933000 70 197.50000
## 2212 NA 2.833333 0.006667000 70 154.00000
## 2213 NA 5.800000 0.011364000 70 193.66667
## 2214 1.328100000 2.263333 0.002672000 70 177.66667
## 2215 0.671000000 2.230000 0.002042000 70 127.60000
## 2216 NA 1.750000 0.001870000 70 187.33333
## 2217 0.020000000 2.166667 0.008000000 70 226.50000
## 2218 0.025000000 3.392857 0.010019000 70 211.54546
## 2219 0.586000000 2.954545 0.007906000 70 190.62500
## 2220 NA 3.783333 0.015750000 70 240.91667
## 2221 0.026000000 2.500000 0.004180000 70 91.00000
## 2222 NA 4.006667 0.007636000 70 203.00000
## 2223 0.047000000 NA 0.002025000 70 198.00000
## 2224 NA 3.850000 0.009124000 70 188.83333
## 2225 0.026000000 NA 0.000960000 70 135.00000
## 2226 NA 2.750000 0.012250000 70 239.50000
## 2227 0.030000000 NA 0.001000000 70 174.00000
## 2228 0.025000000 3.156250 0.008500000 70 176.73333
## 2229 0.020000000 2.884615 0.010538000 70 207.30769
## 2230 NA 2.980000 0.018300000 70 203.60000
## 2231 0.240000000 2.409091 0.010456000 70 228.62500
## 2232 0.095828571 2.255000 0.004455000 70 NA
## 2233 0.034435000 NA 0.001960000 70 216.00000
## 2234 NA 3.190909 0.010046000 70 237.40000
## 2235 0.027500000 2.833333 0.011111000 70 228.87500
## 2236 0.026000000 3.040000 0.002364000 70 NA
## 2237 0.026000000 NA 0.002015000 70 153.50000
## 2238 NA 3.915789 0.017429000 70 267.00000
## 2239 0.004500000 4.007143 0.008971000 70 214.66667
## 2240 0.025000000 3.000000 0.014182000 70 204.45454
## 2241 0.024500000 2.025000 0.001443000 70 169.00000
## 2242 0.025000000 3.208333 0.011818000 70 207.81818
## 2243 NA 2.944444 0.016222000 70 208.33333
## 2244 0.030000000 3.541667 0.006000000 70 150.83333
## 2245 NA 1.950000 0.000615000 70 NA
## 2246 NA 3.550000 0.012714000 70 NA
## 2247 0.026000000 2.328571 0.001727000 70 156.28571
## 2248 0.400000000 2.823529 0.012857000 70 238.47059
## 2249 1.651500000 4.195714 0.004050000 70 NA
## 2250 NA 2.166667 0.002153000 70 139.50000
## 2251 0.025000000 3.454545 0.017727000 70 204.18182
## 2252 0.047000000 NA 0.002105000 70 155.50000
## 2253 1.617500000 2.314000 0.004700000 70 138.20000
## 2254 NA 5.593333 0.017636000 70 NA
## 2255 0.025000000 4.038462 0.018665000 70 286.40000
## 2256 NA 6.877273 0.017222000 70 234.00000
## 2257 0.017260000 NA 0.002395000 70 278.00000
## 2258 0.004000000 3.513333 0.010273000 70 264.00000
## 2259 NA 3.000000 0.019900000 70 279.00000
## 2260 0.500000000 4.000000 0.005000000 70 134.90000
## 2261 0.030000000 3.346154 0.008692000 70 188.07692
## 2262 NA 3.750000 0.014000000 70 NA
## 2263 NA 3.675000 0.006867000 70 169.20000
## 2264 NA 4.222222 0.013667000 70 NA
## 2265 0.034400000 NA NA 70 NA
## 2266 NA 4.065834 0.007928000 70 203.00000
## 2267 NA 3.727273 0.015182000 70 210.49091
## 2268 1.108500000 2.182000 0.006300000 70 151.40000
## 2269 NA 3.500000 0.012314000 70 210.50000
## 2270 NA 2.300000 0.003250000 70 168.00000
## 2271 NA 1.685000 0.000928000 70 198.83333
## 2272 NA 1.642857 0.001269000 70 197.42857
## 2273 NA 2.583333 0.001000000 70 133.33333
## 2274 NA NA 0.000480000 70 189.66667
## 2275 NA 1.502000 0.000594000 70 NA
## 2276 NA 2.000000 0.001600000 70 179.20000
## 2277 NA 1.816667 0.002167000 70 189.00000
## 2278 NA 1.663333 0.001183000 70 184.50000
## 2279 NA 1.100000 0.001167000 70 159.16667
## 2280 NA 3.000000 0.002833000 70 149.00000
## 2281 NA 1.703333 0.001817000 70 167.16667
## 2282 NA 3.333333 0.013842000 70 206.16667
## 2283 NA 4.031000 0.017054000 70 NA
## 2284 NA 1.833333 0.001833000 70 NA
## 2285 NA 1.916667 0.001333000 70 167.66667
## 2286 NA 1.282857 0.000533000 70 NA
## 2287 NA 2.125000 0.015517000 70 NA
## 2288 NA 1.066667 0.000658000 70 NA
## 2289 NA 1.755556 0.006098000 70 NA
## 2290 0.004000000 4.321000 0.013890000 70 NA
## 2291 NA 5.375000 0.003500000 70 NA
## 2292 NA 2.333333 0.001667000 70 NA
## 2293 NA 2.914286 0.006857000 70 NA
## 2294 NA 1.765000 0.001375000 70 185.50000
## 2295 NA 1.300000 0.000374000 70 NA
## 2296 NA 2.187500 0.007730000 70 187.37500
## 2297 NA 2.550000 0.005768000 70 NA
## 2298 NA 2.166667 0.004000000 70 174.16667
## 2299 NA 2.650000 0.004280000 70 173.60000
## 2300 NA 2.253333 0.002100000 70 196.50000
## 2301 NA 2.214286 0.001286000 70 NA
## 2302 NA 1.392857 0.000524000 70 143.66667
## 2303 NA 2.666667 0.002000000 70 143.48333
## 2304 NA 1.283333 0.001333000 70 158.83333
## 2305 NA 1.238333 0.000587000 70 NA
## 2306 NA NA 0.000585000 70 180.66667
## 2307 NA NA 0.000645000 70 132.00000
## 2308 NA 1.700000 0.000670000 70 150.00000
## 2309 NA 3.333333 0.003333000 70 177.60000
## 2310 NA 1.875000 0.001750000 70 153.75000
## 2311 NA 2.333333 0.002600000 70 139.00000
## 2312 NA 1.700000 0.001500000 70 174.20000
## 2313 NA 2.065000 0.003817000 70 189.66667
## 2314 NA 1.351667 0.000465000 70 168.83333
## 2315 NA 2.000000 0.005261000 70 193.85714
## 2316 NA NA 0.000373000 70 169.28571
## 2317 NA 1.333333 0.001072000 70 154.80000
## 2318 NA NA 0.000610000 70 180.00000
## 2319 NA 1.493333 0.000713000 70 NA
## ammonical_nitrogen_mean dissolved_oxygen_mean hardness_mean nitrate_mean
## 1 0.3431430 9.885714 NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 0.9000000 10.514286 NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## 7 0.5644440 9.125000 NA NA
## 8 0.1820000 10.340000 328.20000 NA
## 9 0.0965000 10.783333 361.75000 NA
## 10 0.2344290 8.500000 378.14286 NA
## 11 0.4320000 NA 314.66667 NA
## 12 NA NA NA NA
## 13 NA NA NA NA
## 14 0.5700000 10.070000 NA NA
## 15 0.5600000 NA NA NA
## 16 0.2000590 10.518750 370.18182 NA
## 17 0.3103330 11.558333 325.12500 NA
## 18 NA NA NA NA
## 19 NA NA NA NA
## 20 0.0742000 10.150000 377.20000 NA
## 21 0.1388330 10.120000 350.50000 8.588750
## 22 NA NA NA NA
## 23 NA NA NA NA
## 24 0.4085000 11.600000 395.00000 NA
## 25 NA NA NA NA
## 26 NA NA NA NA
## 27 NA NA NA NA
## 28 0.7462500 10.466667 NA NA
## 29 NA NA NA NA
## 30 NA NA NA NA
## 31 0.7562500 10.900000 NA NA
## 32 0.6266670 11.122222 NA NA
## 33 0.1778750 10.187500 304.12500 NA
## 34 0.5400000 10.662500 NA NA
## 35 NA NA NA NA
## 36 NA NA NA NA
## 37 0.7057140 NA NA NA
## 38 NA NA NA NA
## 39 NA NA NA NA
## 40 0.9125000 NA NA NA
## 41 0.6420000 10.680000 NA NA
## 42 0.2685000 12.270000 325.00000 9.620500
## 43 NA NA NA NA
## 44 NA NA NA NA
## 45 NA NA NA NA
## 46 NA NA NA NA
## 47 NA NA NA NA
## 48 0.4060000 9.866667 NA NA
## 49 0.3038890 10.411111 320.44444 NA
## 50 NA NA NA NA
## 51 0.8675000 NA NA NA
## 52 NA NA NA NA
## 53 0.9866670 NA 314.66667 NA
## 54 0.6395710 11.085714 NA NA
## 55 NA NA NA NA
## 56 0.5788890 11.311111 NA NA
## 57 0.6188890 12.100000 348.00000 NA
## 58 0.7294550 10.900000 NA NA
## 59 NA NA NA NA
## 60 0.5603330 10.900000 342.66667 NA
## 61 1.1480000 NA NA NA
## 62 NA NA NA NA
## 63 1.1422220 NA NA NA
## 64 0.5638890 11.762500 404.00000 NA
## 65 NA NA NA NA
## 66 0.4237500 9.875000 NA NA
## 67 NA NA NA NA
## 68 NA NA NA NA
## 69 NA NA NA NA
## 70 0.5866670 NA NA NA
## 71 0.2322977 10.913690 346.58929 NA
## 72 0.2225477 11.545238 340.08730 NA
## 73 0.3577270 8.300000 NA NA
## 74 0.3580000 10.040000 374.00000 NA
## 75 0.2328213 10.215476 348.07143 NA
## 76 0.2015000 12.250000 376.83333 NA
## 77 0.3783330 NA NA NA
## 78 0.2414443 8.630000 355.86667 NA
## 79 0.2579223 8.552222 360.54444 NA
## 80 0.5083330 NA NA NA
## 81 0.6822860 6.137500 319.40000 NA
## 82 0.1511430 7.947143 NA 13.061143
## 83 0.2335333 9.421111 348.50000 NA
## 84 0.2260317 9.992064 347.97619 NA
## 85 0.1641670 12.933333 337.16667 7.948333
## 86 0.2105000 11.280000 367.33333 NA
## 87 0.3808335 9.970000 370.66667 NA
## 88 0.2726000 8.540000 360.20000 NA
## 89 0.2240000 11.480000 365.00000 NA
## 90 0.3060000 11.370000 365.00000 12.900000
## 91 1.7344645 6.805357 NA NA
## 92 0.8466670 NA NA NA
## 93 0.2391595 8.745428 325.46875 10.812364
## 94 1.6316670 9.620000 NA NA
## 95 0.6511250 7.422222 328.33333 NA
## 96 0.6604287 6.786574 324.18889 NA
## 97 0.3884447 9.946667 369.55556 NA
## 98 0.5649165 12.056667 379.90000 NA
## 99 0.1320000 12.125000 359.50000 10.360000
## 100 0.5583330 NA NA NA
## 101 0.2916253 11.233928 382.91071 NA
## 102 0.2257223 11.485714 337.26190 NA
## 103 0.4600000 NA NA NA
## 104 0.2874000 9.220000 352.00000 NA
## 105 0.6628570 8.685714 NA NA
## 106 0.1705000 10.015455 332.58333 11.390000
## 107 0.5458330 12.233333 380.00000 NA
## 108 0.3631430 7.850000 377.50000 NA
## 109 0.6835710 12.344444 NA NA
## 110 1.4675000 9.185714 NA NA
## 111 0.6771430 7.600000 NA NA
## 112 0.3104335 8.218333 350.26667 NA
## 113 0.1900000 12.000000 373.00000 NA
## 114 0.2383330 12.280000 363.33333 10.700000
## 115 0.2937500 13.125000 NA 9.302500
## 116 0.4984050 7.208334 343.06667 NA
## 117 0.5320000 NA NA NA
## 118 0.5629165 12.233333 375.16667 NA
## 119 NA NA NA NA
## 120 1.6498330 7.116667 318.00000 NA
## 121 0.2847270 11.272727 346.20000 NA
## 122 0.2651223 8.632222 360.74444 NA
## 123 0.3900667 9.866667 365.91667 NA
## 124 0.2385417 10.500000 347.79167 NA
## 125 0.2305060 11.401190 343.95040 NA
## 126 0.3522220 11.039683 382.82540 NA
## 127 0.1518000 11.424000 NA 9.130000
## 128 0.3119890 11.441667 356.43939 11.125238
## 129 0.3064550 10.433333 NA NA
## 130 0.2318570 10.466667 360.28571 NA
## 131 0.6543215 6.394444 331.73333 NA
## 132 0.2323270 9.761587 348.07143 NA
## 133 0.1146000 9.688000 335.00000 9.616000
## 134 0.2487223 8.552222 359.81111 NA
## 135 0.3920000 11.800000 NA NA
## 136 0.2287677 10.143453 348.39286 NA
## 137 0.5728570 11.580000 NA NA
## 138 0.2500000 11.733333 NA 9.120000
## 139 0.2690445 9.890000 345.90074 11.798364
## 140 0.4766670 5.516667 NA NA
## 141 0.2362630 8.612857 325.93750 10.962000
## 142 0.5585553 12.115555 379.93333 NA
## 143 0.2406670 7.929000 326.56667 10.905889
## 144 0.2389777 8.990000 352.33333 NA
## 145 0.1785380 12.125833 350.58333 10.996667
## 146 0.2092500 12.450000 377.83333 NA
## 147 0.2785000 8.561667 NA 12.326667
## 148 0.2726000 8.540000 360.20000 NA
## 149 1.1000000 NA NA NA
## 150 0.6975000 8.933333 386.00000 NA
## 151 0.4282500 9.955555 340.16667 NA
## 152 0.6708157 6.358333 321.21111 NA
## 153 0.4005710 8.485714 338.85714 NA
## 154 0.2285000 10.825000 366.50000 NA
## 155 0.2307500 11.097500 375.50000 NA
## 156 0.3822917 10.214167 373.33333 NA
## 157 0.2466250 10.700000 350.00000 NA
## 158 0.4633330 NA NA NA
## 159 0.2350000 9.572727 370.66667 NA
## 160 0.2931000 8.860000 358.97500 NA
## 161 0.3339583 11.100595 383.16071 NA
## 162 1.3414290 7.685714 NA NA
## 163 0.6495000 7.111111 326.58333 NA
## 164 0.1441670 10.643333 320.33333 13.700000
## 165 1.8760000 6.920000 NA NA
## 166 0.3644170 11.800000 335.36364 9.078571
## 167 0.2340557 11.269048 337.37302 NA
## 168 0.2214165 10.750000 360.83333 NA
## 169 0.2611670 8.190000 329.53333 10.877778
## 170 0.6630240 6.254630 321.15556 NA
## 171 0.4666670 NA NA NA
## 172 0.3230000 11.137143 383.36190 NA
## 173 NA NA NA NA
## 174 0.3786000 10.374667 375.60000 NA
## 175 0.3176920 11.441667 355.54546 10.973333
## 176 0.2697890 10.250000 347.62500 12.124000
## 177 0.0468330 11.210000 201.83333 2.980000
## 178 0.0466670 12.066667 185.40000 2.538000
## 179 0.0797140 12.014286 NA 2.815714
## 180 0.1184290 10.034286 NA 2.575714
## 181 0.0633000 10.844444 198.00000 NA
## 182 0.1212500 NA 194.40000 NA
## 183 0.0360000 11.300000 NA 2.496667
## 184 0.0673330 10.543333 NA 2.921667
## 185 0.1444440 NA 193.80000 NA
## 186 0.0841430 10.031429 205.28571 2.954286
## 187 0.0516670 9.861667 NA 3.108333
## 188 0.0606670 10.941667 202.66667 NA
## 189 0.0610910 11.527273 187.54546 NA
## 190 0.0461670 9.458333 204.80000 2.466667
## 191 0.0520670 11.266667 NA 3.200000
## 192 0.0310000 11.400000 181.50000 2.778000
## 193 0.1148610 NA 186.00000 NA
## 194 0.0708330 11.254545 217.60000 NA
## 195 0.0460000 9.096667 193.25000 2.518000
## 196 0.0570000 10.200000 NA 2.230000
## 197 0.0730770 12.700000 194.33333 NA
## 198 0.0450000 NA 208.00000 NA
## 199 0.0853850 NA 203.50000 NA
## 200 0.0477140 11.042857 NA 2.978571
## 201 0.1128570 NA 190.66667 NA
## 202 0.0941820 11.963636 203.20000 NA
## 203 0.0711670 12.533333 180.00000 3.543333
## 204 0.0957500 11.433333 183.50000 NA
## 205 0.0690000 11.700000 NA 3.153333
## 206 0.0815830 12.766667 218.00000 NA
## 207 0.0583750 10.661667 192.42857 3.334286
## 208 0.0901670 11.950000 NA 2.575000
## 209 0.0618130 10.792308 195.92308 NA
## 210 0.0461670 11.466667 196.14286 2.703333
## 211 0.0621670 10.936364 204.00000 NA
## 212 0.0697140 10.074286 NA 2.637143
## 213 0.0755560 11.672727 197.20000 NA
## 214 0.0521500 12.633333 NA 3.178333
## 215 0.0360000 10.000000 NA 2.534000
## 216 NA NA NA NA
## 217 0.0763640 12.625000 196.66667 NA
## 218 NA NA NA NA
## 219 0.0800000 8.550000 172.20000 NA
## 220 0.0960000 12.180000 193.33333 NA
## 221 0.0820000 NA NA NA
## 222 NA NA NA NA
## 223 0.0520000 12.700000 186.66667 3.336667
## 224 0.0430000 11.266667 NA 2.532857
## 225 0.0573330 12.955556 175.55556 NA
## 226 0.1415970 NA 193.02500 NA
## 227 0.1140000 NA 202.20000 NA
## 228 0.0735000 10.856667 191.16667 2.960000
## 229 0.0305000 10.875000 206.66667 2.700000
## 230 0.0900000 NA NA NA
## 231 0.0600000 9.833333 191.00000 NA
## 232 0.0554860 10.475714 NA 3.155714
## 233 0.0637860 12.384615 192.76923 NA
## 234 0.0518330 11.583333 NA 2.578333
## 235 0.0725000 11.500000 201.00000 NA
## 236 0.0675000 14.266667 196.66667 NA
## 237 0.0600770 10.730769 192.00000 NA
## 238 0.0740770 10.984615 196.53846 NA
## 239 0.0960000 9.888000 NA 2.730000
## 240 0.1300000 10.966667 205.83333 NA
## 241 0.0540000 11.200000 199.66667 3.683333
## 242 0.0516360 10.860000 190.72727 NA
## 243 0.0487780 10.090909 188.11111 3.057833
## 244 0.0956140 10.125714 NA 2.955714
## 245 0.1175000 NA 186.00000 NA
## 246 0.0860000 NA NA NA
## 247 0.0559170 10.250000 188.75000 NA
## 248 0.0553330 10.298333 NA 2.828333
## 249 0.0900000 NA NA NA
## 250 0.0542860 11.721429 180.35714 NA
## 251 0.1001925 NA 202.60714 NA
## 252 0.0310000 10.550000 NA 2.408333
## 253 0.1054170 11.772727 197.09091 NA
## 254 0.1065740 NA 186.00000 NA
## 255 0.0644290 10.076923 175.00000 NA
## 256 0.0606670 12.050000 NA 2.845000
## 257 0.0802000 11.080000 203.20000 NA
## 258 0.0518750 11.222222 188.50000 3.345000
## 259 0.0566670 11.200000 207.11111 NA
## 260 NA NA NA NA
## 261 NA NA NA NA
## 262 0.0653330 9.843333 NA 0.928333
## 263 NA NA NA NA
## 264 0.0393330 10.401667 NA 0.819167
## 265 NA NA NA NA
## 266 NA NA NA NA
## 267 0.0550000 12.100000 NA NA
## 268 NA NA NA NA
## 269 0.1320000 12.200000 NA NA
## 270 NA NA NA NA
## 271 NA NA NA NA
## 272 0.1277500 12.350000 79.22500 1.300000
## 273 0.0410000 11.066667 NA NA
## 274 0.0477140 10.951429 102.10000 1.001000
## 275 NA NA NA NA
## 276 0.1614170 12.466667 NA NA
## 277 0.0326000 11.062000 NA 0.929800
## 278 NA NA NA NA
## 279 0.1090000 12.680000 NA NA
## 280 0.1056000 11.580000 81.28000 1.480800
## 281 0.0501670 12.083333 NA 1.461000
## 282 NA NA NA NA
## 283 NA NA NA NA
## 284 0.0732860 11.535714 105.18333 1.284286
## 285 0.0648000 12.040000 84.34000 1.530000
## 286 0.0904000 13.460000 97.46000 NA
## 287 NA NA NA NA
## 288 0.0420000 10.910000 91.25714 1.034714
## 289 0.0480000 10.533333 102.95000 1.279000
## 290 NA NA NA NA
## 291 NA NA NA NA
## 292 0.0445830 11.750000 NA 1.830000
## 293 0.1296000 12.200000 101.00000 NA
## 294 0.0458330 10.991667 97.75000 1.346667
## 295 0.0425860 10.492857 NA 1.036000
## 296 NA NA NA NA
## 297 NA NA NA NA
## 298 0.0816670 12.605000 93.23333 NA
## 299 0.0763330 11.400000 NA NA
## 300 0.0400000 10.920000 NA NA
## 301 0.0626000 12.420000 88.32000 1.294800
## 302 0.0800000 10.533333 123.66667 NA
## 303 NA NA NA NA
## 304 NA NA NA NA
## 305 0.0365000 9.886667 104.06667 0.770667
## 306 NA NA NA NA
## 307 NA NA NA NA
## 308 0.0721250 11.462500 NA 1.361375
## 309 0.0300000 10.710000 116.25000 NA
## 310 0.0400000 11.533333 NA NA
## 311 1.2435000 11.346429 330.89286 NA
## 312 1.2428570 7.450000 350.85000 NA
## 313 1.4019260 9.600000 313.20000 NA
## 314 0.2082760 12.579310 351.22222 NA
## 315 0.1916670 9.424000 323.83333 8.659000
## 316 0.8047140 8.337143 286.60000 8.512857
## 317 0.6182000 10.248000 362.40000 9.000000
## 318 0.2593330 10.680000 322.66667 10.600000
## 319 0.2920000 11.147826 350.65217 NA
## 320 0.1016670 9.658000 NA NA
## 321 0.1475000 8.668333 318.16667 NA
## 322 NA NA NA NA
## 323 1.1731670 11.435000 273.50000 8.210000
## 324 NA NA NA NA
## 325 1.6348150 12.323077 339.53846 NA
## 326 0.0668000 9.858000 342.40000 8.008000
## 327 0.3223330 10.165000 352.83333 NA
## 328 2.7583330 7.300000 324.26316 NA
## 329 1.4119350 6.686111 303.85294 NA
## 330 0.1620000 11.280000 344.40000 NA
## 331 1.7838750 9.976923 335.47619 NA
## 332 0.7153570 7.828571 261.96296 NA
## 333 1.6874070 9.176000 288.96296 NA
## 334 0.2550000 8.877143 NA 7.378571
## 335 0.2616000 9.994000 272.20000 NA
## 336 0.7177140 10.280000 306.57143 NA
## 337 1.7763830 NA 306.28571 NA
## 338 0.6760000 9.902857 NA 6.575714
## 339 0.2698570 10.194286 NA NA
## 340 0.9403570 8.370833 366.94444 NA
## 341 NA NA NA NA
## 342 0.1650000 9.471667 311.33333 NA
## 343 1.1448330 8.166667 NA 6.535000
## 344 0.2021670 9.550000 292.66667 NA
## 345 1.5477940 13.051613 342.19355 NA
## 346 0.4744000 8.156000 NA 6.014000
## 347 0.5730000 12.070000 308.00000 6.796000
## 348 2.0698700 10.318182 351.47826 NA
## 349 0.2625000 8.216667 NA 7.851667
## 350 0.1075000 9.933333 NA NA
## 351 0.2363330 9.248333 NA 6.156667
## 352 NA NA NA NA
## 353 0.2737140 10.471429 346.14286 6.893000
## 354 1.0468320 NA 346.75000 NA
## 355 0.1853330 8.651667 NA 8.703333
## 356 0.9585710 9.792857 286.57143 8.680000
## 357 0.3987140 8.524286 NA 7.735714
## 358 2.3108410 12.183333 333.33333 NA
## 359 2.0021740 6.504348 308.84211 NA
## 360 0.6356670 9.583333 NA 7.626667
## 361 3.7031580 NA 362.15789 NA
## 362 0.6879460 10.976923 331.96154 NA
## 363 1.0507460 NA 346.75000 NA
## 364 0.6552380 6.416667 301.71429 NA
## 365 0.2013330 8.100000 NA 6.411667
## 366 1.7424000 5.804000 333.15789 NA
## 367 0.5834620 6.703333 351.36667 NA
## 368 NA NA NA NA
## 369 0.1991670 9.040000 NA NA
## 370 2.0052630 7.759091 349.37500 NA
## 371 0.0933330 9.430000 NA 1.420000
## 372 0.0498330 9.968333 NA 1.780000
## 373 0.6353400 8.860000 NA NA
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## 1809 0.0773330 10.145000 NA 5.045000
## 1810 0.1600000 NA NA NA
## 1811 0.2233330 10.400000 389.00000 NA
## 1812 0.0783330 11.233333 NA NA
## 1813 NA NA NA NA
## 1814 0.1100000 12.150000 NA NA
## 1815 0.1176670 9.483333 390.83333 5.083667
## 1816 0.0834000 11.600000 429.40000 NA
## 1817 0.1048000 10.690000 NA NA
## 1818 0.1700000 11.960000 NA NA
## 1819 0.2574000 9.060000 NA 3.844000
## 1820 0.2183330 NA NA NA
## 1821 0.1387140 11.271429 317.28571 5.680000
## 1822 0.1486670 11.021667 NA 5.190000
## 1823 0.1760000 12.150000 NA NA
## 1824 0.2100000 12.050000 NA NA
## 1825 0.0535000 12.200000 NA 5.095000
## 1826 0.7366670 NA NA NA
## 1827 0.0472500 9.860000 NA 3.735000
## 1828 0.1068330 9.890000 NA 5.693333
## 1829 0.0393330 10.343333 NA 3.798333
## 1830 0.3183330 NA NA NA
## 1831 0.1605000 12.633333 322.83333 NA
## 1832 0.0578290 9.648571 NA 3.732857
## 1833 0.0300000 9.730000 NA 3.473333
## 1834 0.1716670 NA NA NA
## 1835 0.3200000 10.500000 389.00000 NA
## 1836 0.1638330 10.633333 317.33333 5.196667
## 1837 0.1336670 11.026667 397.66667 NA
## 1838 0.0997140 10.757143 NA 3.963333
## 1839 0.1362000 11.300000 458.60000 NA
## 1840 0.1218000 12.550000 NA 5.225000
## 1841 NA NA NA NA
## 1842 0.0720000 10.521111 389.20000 5.770000
## 1843 0.0730000 9.282857 NA NA
## 1844 0.1183330 12.633333 NA NA
## 1845 0.0400000 10.766667 NA NA
## 1846 0.0512860 8.227143 349.28571 3.608571
## 1847 0.2156500 10.966667 415.00000 NA
## 1848 0.1403330 11.166667 324.00000 NA
## 1849 0.0833330 9.900000 NA NA
## 1850 0.0466670 10.900000 NA NA
## 1851 0.1438330 11.683333 NA 12.500000
## 1852 0.0336670 11.428333 387.50000 11.405000
## 1853 0.3255000 9.340000 430.50000 13.680000
## 1854 0.8280000 NA NA NA
## 1855 0.1466670 10.633333 NA NA
## 1856 0.0712500 11.200000 NA NA
## 1857 0.0475710 11.842857 400.00000 NA
## 1858 0.3833330 NA NA NA
## 1859 0.8642860 12.566667 NA NA
## 1860 0.1025000 12.900000 NA NA
## 1861 0.0560000 9.950000 NA NA
## 1862 0.0590500 9.293333 NA 9.708333
## 1863 0.4320000 12.800000 NA NA
## 1864 0.2840000 13.100000 NA NA
## 1865 0.0344000 10.556000 421.00000 13.480000
## 1866 0.0480000 11.500000 394.00000 NA
## 1867 0.8450000 NA NA NA
## 1868 0.1826670 11.366667 NA NA
## 1869 0.1557140 NA NA NA
## 1870 0.0310000 8.860000 NA 9.075000
## 1871 0.0690000 9.728333 NA 10.711667
## 1872 0.2102860 12.514286 NA NA
## 1873 0.2005000 11.883333 408.33333 NA
## 1874 0.2510000 10.600000 428.40000 NA
## 1875 0.1213330 12.166667 410.50000 12.633333
## 1876 0.0748000 9.400000 NA 9.514000
## 1877 0.0904290 12.264286 442.71429 11.727143
## 1878 0.1128570 12.428571 NA NA
## 1879 0.0752000 9.984000 NA 11.033333
## 1880 0.1530000 11.933333 NA NA
## 1881 0.1113000 11.780000 NA 12.060000
## 1882 0.1974000 8.540000 423.40000 10.246000
## 1883 0.1104000 10.816000 448.20000 16.100000
## 1884 0.0430170 10.235000 NA 9.315000
## 1885 0.6312500 NA NA NA
## 1886 0.2450000 11.800000 NA NA
## 1887 0.0918330 10.460000 382.33333 NA
## 1888 0.2128570 10.150000 NA NA
## 1889 0.1238330 10.233333 NA NA
## 1890 0.0718330 11.501250 NA 13.026667
## 1891 0.9183330 12.900000 NA NA
## 1892 0.1013330 11.535000 NA 12.350000
## 1893 0.2150000 9.833333 NA NA
## 1894 0.0665000 11.483333 NA 10.841667
## 1895 0.1025000 10.766667 385.50000 NA
## 1896 0.1463330 11.800000 406.50000 13.650000
## 1897 0.7400000 NA NA NA
## 1898 0.0653330 12.350000 NA 12.750000
## 1899 0.2583330 10.200000 NA NA
## 1900 0.5083330 11.760000 NA NA
## 1901 0.0806500 11.980000 NA 10.263833
## 1902 0.0710000 12.400000 NA 13.600000
## 1903 0.0873330 11.075000 373.33333 10.023333
## 1904 0.2166670 9.900000 NA NA
## 1905 0.0738330 10.310000 NA 9.736667
## 1906 0.0585710 8.225000 NA NA
## 1907 0.0788000 11.120000 142.20000 NA
## 1908 0.0550000 11.657143 142.14286 4.527143
## 1909 0.0300000 11.366667 NA NA
## 1910 0.2240000 NA NA NA
## 1911 0.0400000 10.666667 156.83333 NA
## 1912 0.0750000 NA NA NA
## 1913 0.0783330 NA NA NA
## 1914 0.0450000 12.575000 NA 3.630000
## 1915 0.0500000 NA NA NA
## 1916 0.0316670 9.918333 NA 3.118333
## 1917 0.0600000 11.883333 NA NA
## 1918 0.0571430 12.171429 NA 3.075000
## 1919 0.0451670 11.383333 136.00000 NA
## 1920 NA NA 122.00000 NA
## 1921 0.0487500 12.314286 NA NA
## 1922 0.0550000 14.150000 NA NA
## 1923 0.0417140 10.714286 173.71429 NA
## 1924 0.0340000 10.428571 147.20000 NA
## 1925 0.0440000 10.400000 151.20000 4.421000
## 1926 NA NA NA NA
## 1927 0.0750000 13.150000 NA NA
## 1928 NA NA NA NA
## 1929 0.0498570 11.385714 NA NA
## 1930 0.1260000 10.350000 131.56000 NA
## 1931 0.0660000 8.450000 NA NA
## 1932 0.0427630 11.625000 NA 4.456250
## 1933 0.0550000 11.400000 NA NA
## 1934 0.0400000 12.250000 NA NA
## 1935 0.0833330 9.998333 NA 4.130000
## 1936 0.1400000 NA NA NA
## 1937 0.1250000 12.583333 NA NA
## 1938 0.0400000 13.120000 NA NA
## 1939 0.1004000 12.360000 221.00000 NA
## 1940 0.0400000 11.200000 NA NA
## 1941 0.0565710 10.342857 149.42857 NA
## 1942 0.1373330 11.566667 129.33333 NA
## 1943 0.0850000 11.083333 174.16667 NA
## 1944 0.0801430 11.450000 126.85714 4.390000
## 1945 NA NA NA NA
## 1946 NA NA NA NA
## 1947 0.0566670 11.550000 NA NA
## 1948 0.0372110 10.017778 NA 3.894444
## 1949 0.0838000 12.280000 151.20000 NA
## 1950 0.0806000 10.480000 NA NA
## 1951 NA NA NA NA
## 1952 0.1121670 11.585714 155.75000 4.716667
## 1953 0.1228570 12.014286 130.62857 NA
## 1954 0.0533330 NA NA NA
## 1955 0.0525000 NA NA NA
## 1956 NA NA NA NA
## 1957 0.1014290 10.750000 NA NA
## 1958 0.0510000 9.723333 140.15000 3.958333
## 1959 0.0365000 11.133333 145.50000 4.310000
## 1960 0.0631430 9.991429 NA 13.298571
## 1961 0.0651670 12.016667 629.75000 12.716667
## 1962 0.0518890 9.862500 NA NA
## 1963 0.0448570 8.941667 511.85714 NA
## 1964 0.0614290 11.300000 NA NA
## 1965 0.1041430 10.825000 NA NA
## 1966 0.0618570 11.128571 NA 15.471429
## 1967 0.0395710 9.074286 525.00000 NA
## 1968 0.0721000 11.425714 NA 15.342857
## 1969 0.0855000 11.550000 NA NA
## 1970 0.0671670 11.383333 537.50000 14.883333
## 1971 0.0890000 11.500000 NA NA
## 1972 0.0600000 10.915714 NA 15.142857
## 1973 0.0456250 NA NA NA
## 1974 0.0578000 11.800000 NA 16.100000
## 1975 0.0673330 11.250000 556.00000 15.016667
## 1976 0.1118330 10.274000 NA 15.050000
## 1977 0.0760000 12.560000 NA NA
## 1978 0.1865710 11.214286 NA NA
## 1979 0.0683330 13.400000 708.66667 NA
## 1980 0.0990000 11.616667 NA NA
## 1981 0.1116670 NA NA NA
## 1982 0.1500000 11.880000 NA NA
## 1983 0.1450000 NA NA NA
## 1984 0.0466000 10.200000 648.40000 NA
## 1985 0.0808330 NA NA NA
## 1986 NA NA NA NA
## 1987 0.0510000 10.542857 NA 14.242857
## 1988 0.0601670 10.880000 NA 14.050000
## 1989 0.0967500 9.675000 650.50000 NA
## 1990 0.0853330 11.383333 608.83333 NA
## 1991 0.1106000 11.100000 NA 14.398000
## 1992 0.0510000 11.640000 582.40000 11.043333
## 1993 0.0575000 11.983333 NA NA
## 1994 0.1115710 11.471429 NA NA
## 1995 0.0493330 10.070000 NA 14.866667
## 1996 0.0350000 9.930000 NA 14.000000
## 1997 0.0674000 11.900000 606.00000 NA
## 1998 0.0585000 10.396667 NA 13.766667
## 1999 0.0534000 10.198333 NA 14.883333
## 2000 0.0353330 10.800000 626.00000 NA
## 2001 0.1216670 11.550000 NA NA
## 2002 0.3100000 NA NA NA
## 2003 0.0700000 11.100000 NA NA
## 2004 0.0388330 11.416667 651.66667 NA
## 2005 0.0735000 11.400000 NA NA
## 2006 0.0630670 10.066667 NA 14.083333
## 2007 0.0500000 10.914286 NA NA
## 2008 0.0606670 11.050000 NA 15.550000
## 2009 0.2240000 NA NA NA
## 2010 0.1314290 10.628571 NA NA
## 2011 0.1083330 10.600000 NA NA
## 2012 0.0396000 9.683333 602.83333 15.550000
## 2013 0.1194000 9.582000 544.40000 12.976000
## 2014 0.0831670 11.083333 NA NA
## 2015 0.0441670 9.500000 608.83333 NA
## 2016 0.0322860 8.401429 505.85714 NA
## 2017 NA NA NA NA
## 2018 0.0787500 11.562857 581.62500 NA
## 2019 0.0880000 11.580000 369.60000 NA
## 2020 0.0576670 11.383333 415.16667 10.213333
## 2021 0.0310000 10.050000 NA 9.088000
## 2022 0.1385710 10.314286 541.42857 NA
## 2023 0.2136360 NA 468.00000 NA
## 2024 0.1096670 10.766667 480.50000 NA
## 2025 0.1918330 11.011667 NA 8.093333
## 2026 0.0880000 10.680000 448.60000 NA
## 2027 0.0311670 11.018182 437.66667 NA
## 2028 0.0347500 9.743333 NA 9.675000
## 2029 0.1745000 9.651667 NA 6.525000
## 2030 0.2921430 9.025000 517.33333 NA
## 2031 0.0412500 9.482500 439.16667 11.150000
## 2032 0.0433330 9.893333 461.66667 8.886500
## 2033 0.0434290 9.412857 413.85714 9.877143
## 2034 0.0628570 9.407143 476.14286 NA
## 2035 0.1495000 9.333333 412.66667 NA
## 2036 0.9076670 11.550000 444.50000 12.450000
## 2037 0.0858890 12.437500 420.88889 NA
## 2038 0.1132000 10.830000 372.36364 NA
## 2039 0.1439420 12.172727 477.91667 NA
## 2040 0.2500000 NA 388.66667 NA
## 2041 0.0446670 10.773333 449.66667 NA
## 2042 0.0828570 11.438571 NA 7.020000
## 2043 0.0328330 9.758333 NA 4.463333
## 2044 0.1926670 8.128571 592.14286 NA
## 2045 0.0858890 12.437500 420.88889 NA
## 2046 0.1900000 9.810000 NA 10.151667
## 2047 0.6042860 NA 426.42857 NA
## 2048 0.3490000 NA 383.25000 NA
## 2049 0.0857140 9.400000 528.85714 NA
## 2050 0.0324000 8.738000 NA 5.045000
## 2051 0.0702000 11.800000 NA 9.678000
## 2052 0.1713900 14.288889 441.10000 NA
## 2053 0.2388890 10.944444 479.16667 NA
## 2054 0.0625710 9.380000 NA 6.452500
## 2055 0.0966670 10.145455 580.41667 NA
## 2056 0.1517650 10.229412 463.23529 NA
## 2057 0.0418570 11.445714 421.00000 9.281667
## 2058 0.1010500 11.350000 NA 10.916667
## 2059 0.0540000 8.673333 NA 6.298000
## 2060 0.0517690 10.533333 454.61539 NA
## 2061 0.0440000 8.168571 NA 7.520000
## 2062 0.1292000 10.840000 427.25000 12.517500
## 2063 0.0668000 10.710000 415.75000 11.546000
## 2064 0.0661430 10.860000 NA 7.327143
## 2065 0.0756000 13.850000 478.20000 NA
## 2066 0.0446000 11.148000 NA 7.272000
## 2067 0.0547140 10.871429 459.57143 NA
## 2068 0.2041670 11.006667 NA 10.113333
## 2069 0.0587140 10.388571 383.14286 10.757143
## 2070 0.0502000 9.562000 NA 7.800000
## 2071 0.0901670 11.343333 447.83333 NA
## 2072 0.0481820 9.020000 468.00000 NA
## 2073 0.0300000 10.180000 NA 6.892500
## 2074 0.1825000 10.285714 489.62500 NA
## 2075 0.0881820 10.620000 490.18182 NA
## 2076 0.1154670 15.316667 474.16667 NA
## 2077 0.0811110 11.177778 NA NA
## 2078 0.0971670 11.700000 185.83333 NA
## 2079 0.0883330 NA NA NA
## 2080 0.0590000 11.066667 NA NA
## 2081 0.0646360 10.540000 NA NA
## 2082 0.0965000 11.966667 NA NA
## 2083 0.0811110 11.177778 NA NA
## 2084 0.2983330 NA NA NA
## 2085 0.1133330 10.900000 NA NA
## 2086 0.1500000 12.450000 NA NA
## 2087 0.1570000 12.333333 NA NA
## 2088 0.1220000 12.266667 NA 4.051667
## 2089 0.1228570 NA NA NA
## 2090 0.2112500 13.350000 NA NA
## 2091 0.0681430 11.866667 NA NA
## 2092 0.0954290 9.185714 175.28571 NA
## 2093 0.0886670 12.400000 157.00000 3.322000
## 2094 NA NA NA NA
## 2095 0.0775000 10.620000 151.00000 NA
## 2096 0.0300000 12.100000 NA 3.116667
## 2097 0.0623330 11.900000 NA 4.368333
## 2098 0.0726670 12.400000 NA NA
## 2099 0.0300000 10.000000 NA 3.592000
## 2100 0.0330000 9.710000 NA 3.546667
## 2101 0.0506670 11.533333 NA 2.955000
## 2102 0.0594000 11.400000 NA NA
## 2103 0.0560000 10.742857 185.71429 NA
## 2104 0.1568330 12.733333 NA NA
## 2105 0.0787500 10.175000 NA NA
## 2106 0.1692860 10.878571 NA NA
## 2107 0.1690000 12.714286 NA NA
## 2108 0.0300000 13.500000 149.66667 3.496667
## 2109 0.3172500 NA NA NA
## 2110 0.1132500 11.750000 148.50000 NA
## 2111 0.1700000 NA NA NA
## 2112 0.0565710 10.600000 178.00000 5.022000
## 2113 0.0777140 9.884286 NA 4.432857
## 2114 0.1075000 11.850000 NA NA
## 2115 0.0580000 10.033333 196.16667 NA
## 2116 0.0610000 12.600000 NA 4.056667
## 2117 0.0850000 11.700000 NA NA
## 2118 0.3425000 NA NA NA
## 2119 0.0825560 10.733333 NA NA
## 2120 0.1248165 12.606666 NA NA
## 2121 0.1854000 12.700000 NA NA
## 2122 0.1145000 11.233333 183.33333 NA
## 2123 0.0350000 10.800000 166.00000 4.840000
## 2124 0.2644440 12.000000 NA NA
## 2125 NA NA NA NA
## 2126 0.0435000 10.028333 NA 3.468333
## 2127 0.0863330 9.052857 387.16667 11.230000
## 2128 0.0920000 8.896667 373.00000 11.070000
## 2129 0.1171670 9.240000 333.50000 11.038333
## 2130 0.1866670 11.503333 405.00000 11.036667
## 2131 0.2725710 9.592857 465.14286 13.985714
## 2132 0.3712000 NA 494.67692 NA
## 2133 0.3056000 10.290000 558.88571 14.842857
## 2134 0.1106920 12.166667 493.16667 10.800000
## 2135 0.4622220 NA 508.60000 NA
## 2136 0.6963640 11.122222 494.44444 NA
## 2137 0.1774230 11.484000 547.22286 14.425000
## 2138 0.0849290 10.585714 481.85714 14.250000
## 2139 0.1381670 7.938333 379.50000 10.481667
## 2140 NA NA NA NA
## 2141 0.0374000 10.154000 NA 11.580000
## 2142 0.0609000 9.950000 NA 10.766000
## 2143 0.0837390 10.320833 399.77778 12.150000
## 2144 0.4266540 12.111538 528.83333 13.944444
## 2145 0.2508180 12.372727 532.30769 14.983333
## 2146 0.0447140 8.616000 422.60000 14.060000
## 2147 0.0935000 10.675000 415.25000 11.600000
## 2148 0.3750000 NA 491.25000 NA
## 2149 0.1756840 10.831579 481.23077 13.850000
## 2150 0.1930430 NA 491.36364 NA
## 2151 0.0358000 9.448000 327.00000 11.412000
## 2152 0.0832860 9.867143 NA 11.400000
## 2153 0.1670000 10.266667 NA 10.851667
## 2154 0.3065000 12.195000 572.64286 15.420000
## 2155 0.2670770 11.435294 404.69231 13.315714
## 2156 0.1609000 9.877778 452.00000 15.500800
## 2157 0.0957500 12.200000 438.25000 12.750000
## 2158 0.0565000 9.288333 NA 9.735000
## 2159 0.0797140 6.977143 358.50000 9.457143
## 2160 0.1738750 11.333333 427.28571 11.441250
## 2161 0.1042860 11.254286 NA 11.871429
## 2162 0.0858330 9.785000 NA 12.141667
## 2163 0.5375000 NA 488.40000 NA
## 2164 0.0857930 10.528571 546.56250 13.628571
## 2165 0.0521670 7.763333 392.50000 11.231667
## 2166 0.1887140 11.290000 465.53333 13.200000
## 2167 0.1156800 10.792000 NA 13.320000
## 2168 0.0608180 8.672727 427.10000 12.608143
## 2169 0.1266670 10.496000 445.50000 15.700000
## 2170 0.0691000 10.240000 NA 11.328571
## 2171 0.4848280 NA 482.90000 NA
## 2172 0.2353040 10.995833 494.46154 14.200000
## 2173 0.0779230 9.276923 375.16667 11.245714
## 2174 0.2930770 NA 489.44444 NA
## 2175 0.3330000 10.768966 466.27778 NA
## 2176 0.0738330 6.295000 394.00000 7.925000
## 2177 0.1340000 9.820833 436.43750 12.344000
## 2178 0.1805000 10.735714 NA 13.333333
## 2179 0.6119230 12.446667 523.83333 NA
## 2180 0.0550000 9.030000 NA 15.800000
## 2181 0.1736000 9.858333 491.61539 NA
## 2182 0.0412860 10.131250 NA 9.838571
## 2183 0.0947140 10.343750 365.15385 12.622714
## 2184 0.1328330 10.115000 385.00000 11.800000
## 2185 0.0931670 10.868571 414.33333 12.011667
## 2186 0.4770590 NA 517.36000 NA
## 2187 0.1121430 11.010000 NA 11.604286
## 2188 0.1330000 9.601667 NA 9.453333
## 2189 0.2011850 10.615385 489.60000 18.785714
## 2190 0.4260870 12.827273 503.75000 NA
## 2191 0.0884570 12.057143 NA 13.642857
## 2192 0.2558330 10.491667 NA 11.100000
## 2193 0.1118330 11.225000 410.00000 12.411667
## 2194 0.2498570 12.314286 411.54546 13.700000
## 2195 0.2614290 NA 505.71429 NA
## 2196 0.0876670 10.830000 394.00000 13.900000
## 2197 0.1709090 11.891304 510.41667 14.500000
## 2198 0.0338330 9.375000 NA 10.538333
## 2199 0.0761670 9.146667 416.66667 12.833333
## 2200 0.1481670 9.216667 268.83333 7.253333
## 2201 0.4006670 11.866667 213.33333 6.525000
## 2202 1.1627270 NA 349.00000 NA
## 2203 0.8736360 NA 349.00000 NA
## 2204 0.3963330 9.433333 329.83333 NA
## 2205 1.1000000 NA NA NA
## 2206 1.0690910 NA 352.00000 NA
## 2207 0.2040000 11.700000 NA 6.970000
## 2208 1.2500000 NA NA NA
## 2209 NA NA NA NA
## 2210 0.7256250 11.007143 299.16667 NA
## 2211 0.0921670 9.736667 NA 7.825000
## 2212 0.3845000 12.563333 230.33333 NA
## 2213 0.9061540 NA 323.33333 NA
## 2214 0.1785000 9.161667 283.16667 9.370000
## 2215 0.5304000 12.080000 225.40000 7.200000
## 2216 0.0981250 9.397500 301.66667 NA
## 2217 0.3245000 10.012500 299.50000 NA
## 2218 0.8421430 11.335714 314.25000 NA
## 2219 0.8254550 12.650000 318.00000 NA
## 2220 0.6814170 9.391667 312.28571 NA
## 2221 0.7600000 11.148000 152.50000 NA
## 2222 0.6506670 12.271429 292.14286 NA
## 2223 0.1110000 9.790000 NA 5.345000
## 2224 0.7240000 11.230000 272.50000 NA
## 2225 0.0933330 11.300000 217.00000 4.465000
## 2226 0.4936670 9.350000 287.91667 NA
## 2227 0.1360000 12.200000 232.25000 5.120000
## 2228 0.5266000 10.600000 267.85714 NA
## 2229 0.5384620 9.423077 284.23077 NA
## 2230 1.1375000 10.460000 301.77778 NA
## 2231 0.5118180 9.800000 338.00000 NA
## 2232 0.1969630 8.896250 NA 8.128750
## 2233 0.0920000 8.750000 NA 6.320000
## 2234 0.6466670 9.257143 332.20000 NA
## 2235 0.7996670 10.655556 336.60000 NA
## 2236 0.1332000 9.818000 NA NA
## 2237 0.1325000 9.380000 245.33333 4.505000
## 2238 0.7426320 NA 383.00000 NA
## 2239 0.5742860 10.407692 322.50000 NA
## 2240 0.6319090 10.145455 298.60000 NA
## 2241 0.1495000 11.666667 NA 6.380000
## 2242 0.5574550 10.730000 290.40000 NA
## 2243 0.5707780 8.655556 276.00000 NA
## 2244 0.5145000 11.508333 236.00000 NA
## 2245 0.0606670 11.183333 NA NA
## 2246 0.7560000 NA NA NA
## 2247 0.0858570 9.232857 NA 6.348571
## 2248 0.5035290 9.950000 295.28571 NA
## 2249 0.4771430 10.884286 NA 7.141429
## 2250 0.1940000 12.118333 NA 5.311667
## 2251 0.6328180 9.160000 274.33333 NA
## 2252 0.2425000 11.100000 NA 4.050000
## 2253 0.4120000 10.940000 228.75000 NA
## 2254 1.1533330 NA NA NA
## 2255 0.7969230 8.591667 346.66667 NA
## 2256 1.2408635 NA 349.00000 NA
## 2257 0.0875000 9.020000 NA 6.530000
## 2258 0.5626670 9.508333 354.16667 NA
## 2259 1.2700000 8.760000 330.00000 NA
## 2260 0.7125000 11.266667 256.60000 NA
## 2261 0.5131540 11.007692 269.42857 NA
## 2262 1.1000000 NA NA NA
## 2263 0.6742860 11.300000 291.60000 NA
## 2264 0.9955560 NA NA NA
## 2265 NA NA NA NA
## 2266 0.6643960 11.585714 292.14286 NA
## 2267 0.8935450 9.950000 279.40000 NA
## 2268 0.3034000 8.670000 237.00000 NA
## 2269 0.6400000 12.057143 NA NA
## 2270 0.2640000 11.775000 NA NA
## 2271 0.1421670 10.888333 502.00000 5.160000
## 2272 0.0714290 10.228571 NA NA
## 2273 0.1130000 10.180000 NA NA
## 2274 0.0400000 9.318333 NA 8.783333
## 2275 0.0736800 11.360000 NA 4.598000
## 2276 0.0740000 9.980000 NA NA
## 2277 0.0883330 9.616667 506.00000 NA
## 2278 0.1111670 9.590000 509.83333 NA
## 2279 0.0665000 9.611667 666.83333 3.585500
## 2280 0.2751670 11.683333 NA NA
## 2281 0.2246670 11.516667 573.16667 7.276000
## 2282 0.6533330 12.333333 NA NA
## 2283 1.2360000 7.777778 NA NA
## 2284 0.1561670 11.550000 NA NA
## 2285 0.0470000 9.515000 753.16667 NA
## 2286 0.0607140 10.004286 NA 4.721429
## 2287 0.9240000 8.750000 NA NA
## 2288 0.0360000 9.305000 NA 9.465000
## 2289 0.3144440 8.228571 NA NA
## 2290 1.1430000 9.155556 NA NA
## 2291 0.3930000 9.925000 NA NA
## 2292 0.1680000 11.883333 NA NA
## 2293 0.5828570 NA NA NA
## 2294 0.1422500 12.020000 501.50000 NA
## 2295 0.0410000 11.260000 NA 5.980000
## 2296 0.3675000 10.562500 NA NA
## 2297 0.5533330 10.566667 NA NA
## 2298 0.3700000 11.160000 NA NA
## 2299 0.4040000 12.044444 NA NA
## 2300 0.3386670 9.043333 545.50000 NA
## 2301 0.0675710 10.900000 NA NA
## 2302 0.0656710 10.515714 NA 3.891667
## 2303 0.3355000 11.216667 778.00000 NA
## 2304 0.1636670 11.106667 648.66667 NA
## 2305 0.0370000 9.105000 NA 8.728333
## 2306 0.0386670 9.263333 NA 6.970000
## 2307 0.0720000 10.225000 NA 2.725000
## 2308 0.0960000 10.924286 NA 5.532857
## 2309 0.2139170 9.500000 NA NA
## 2310 0.2380000 10.900000 572.25000 5.536750
## 2311 0.2413330 14.100000 678.83333 NA
## 2312 0.0554000 9.775000 729.00000 NA
## 2313 0.3250000 9.720000 480.16667 NA
## 2314 0.0331670 9.641667 NA 6.171667
## 2315 0.4057140 11.614286 NA NA
## 2316 0.0460000 11.271429 NA 5.240000
## 2317 0.1086250 11.125000 NA 4.250000
## 2318 0.0300000 8.875000 528.00000 6.995000
## 2319 0.0350000 9.260000 NA 3.853333
## nitrite_mean orthophosphate_mean oxygen_saturation_mean pH_mean
## 1 NA NA NA 8.257143
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA 7.788889
## 5 NA NA NA NA
## 6 NA NA NA NA
## 7 NA NA NA 7.933333
## 8 NA 1.7212000 99.60000 7.957143
## 9 0.1005000 1.2300000 NA 8.333333
## 10 0.1051430 NA 83.00000 8.100000
## 11 NA 1.5400000 NA 7.900000
## 12 NA NA NA NA
## 13 NA NA NA NA
## 14 NA NA NA 8.010000
## 15 NA NA NA 7.987500
## 16 0.0981430 1.5697500 NA 8.200000
## 17 0.1270000 0.7970000 NA 7.816667
## 18 NA NA NA NA
## 19 NA NA NA NA
## 20 NA 2.5740000 102.00000 8.300000
## 21 0.1212500 1.4520000 99.20000 8.100000
## 22 NA NA NA NA
## 23 NA NA NA NA
## 24 NA 1.6500000 94.16667 7.933333
## 25 NA NA NA NA
## 26 NA NA NA NA
## 27 NA NA NA NA
## 28 NA NA NA 7.850000
## 29 NA NA NA NA
## 30 NA NA NA NA
## 31 NA NA NA 7.712500
## 32 NA NA NA 7.955556
## 33 NA 1.5875000 105.62500 8.100000
## 34 NA NA NA 7.987500
## 35 NA NA NA NA
## 36 NA NA NA NA
## 37 NA NA NA 7.957143
## 38 NA NA NA NA
## 39 NA NA NA NA
## 40 NA NA NA 7.912500
## 41 NA NA NA 7.820000
## 42 0.1095000 0.8595000 97.00000 7.900000
## 43 NA NA NA NA
## 44 NA NA NA NA
## 45 NA NA NA NA
## 46 NA NA NA NA
## 47 NA NA NA NA
## 48 NA NA NA 8.000000
## 49 0.1114440 NA 54.00000 7.900000
## 50 NA NA NA NA
## 51 NA NA NA 7.737500
## 52 NA NA NA NA
## 53 NA 1.5400000 NA 7.811111
## 54 NA NA NA 8.100000
## 55 NA NA NA NA
## 56 NA NA NA 7.811111
## 57 NA 1.9100000 NA 7.933333
## 58 NA NA NA 7.818182
## 59 NA NA NA NA
## 60 NA 2.3376670 93.00000 7.900000
## 61 NA NA NA 7.860000
## 62 NA NA NA NA
## 63 NA NA NA 7.933333
## 64 NA 1.8200000 NA 8.000000
## 65 NA NA NA NA
## 66 NA NA NA 7.900000
## 67 NA NA NA NA
## 68 NA NA NA NA
## 69 NA NA NA NA
## 70 NA NA NA 7.766667
## 71 NA 1.4293570 98.05556 8.014286
## 72 NA 1.2796110 98.96667 8.039682
## 73 NA NA NA 8.000000
## 74 NA 4.1804000 90.60000 7.976000
## 75 NA 1.6643570 95.44444 7.954762
## 76 NA 1.4050835 98.83333 8.058333
## 77 NA NA NA 7.520000
## 78 NA 3.1327890 NA 7.914444
## 79 0.1280000 3.9784667 NA 7.992222
## 80 NA NA NA 7.660000
## 81 NA 5.3740000 66.25000 7.785714
## 82 0.1263570 0.7797140 82.42857 7.864286
## 83 NA 2.1695447 95.00000 7.887778
## 84 NA 1.7136030 95.00000 7.909524
## 85 0.0552170 0.4770000 109.83333 8.250000
## 86 NA 4.0426670 108.20000 8.166667
## 87 NA 3.9753665 89.71667 7.978000
## 88 0.1280000 4.4750000 NA 8.000000
## 89 NA 2.8643330 97.20000 8.050000
## 90 0.0843330 1.9257270 95.28571 8.063636
## 91 NA NA NA 7.567857
## 92 NA NA NA 7.716667
## 93 0.1213090 2.9592535 81.82857 7.897222
## 94 NA NA NA 7.633333
## 95 NA 4.5966670 74.55556 7.900000
## 96 NA 4.9846667 70.63889 7.836905
## 97 NA 3.9070220 89.42222 7.978667
## 98 NA 1.6707500 97.41667 8.106666
## 99 0.0603750 1.5392500 102.37500 8.262500
## 100 NA NA NA 7.850000
## 101 NA 2.3087855 97.62500 8.073571
## 102 NA 1.4813650 98.68333 8.047619
## 103 NA NA NA 7.883333
## 104 NA 4.9080000 93.60000 7.980000
## 105 NA NA NA 7.728571
## 106 0.0900000 2.7200000 97.54546 8.141667
## 107 NA 1.7325000 98.83333 8.133333
## 108 NA 3.4350000 NA 7.957143
## 109 NA NA NA 8.021429
## 110 NA NA NA 7.612500
## 111 NA NA NA 7.571429
## 112 NA 3.3901665 75.01667 7.881666
## 113 NA 1.3615000 98.00000 8.050000
## 114 0.0960000 1.1100000 101.50000 7.966667
## 115 0.0541750 0.5007500 105.75000 8.210000
## 116 NA 4.0181665 69.41667 7.834524
## 117 NA NA NA 7.560000
## 118 NA 2.3766665 102.83333 8.150000
## 119 NA NA NA NA
## 120 NA 6.6250000 72.33333 7.816667
## 121 0.1127800 NA NA 8.045455
## 122 0.1280000 4.2267333 NA 8.005556
## 123 NA 2.2570000 83.98333 7.961667
## 124 NA 1.6149167 96.86111 7.991667
## 125 NA 1.2635513 99.25000 8.033730
## 126 NA 3.0128257 97.22222 8.060317
## 127 0.0634600 0.5342000 94.40000 8.054000
## 128 0.1027020 2.0341595 96.33333 8.047349
## 129 NA NA NA 8.118182
## 130 NA 4.1342860 100.16667 8.114286
## 131 NA 4.4915000 65.44444 7.799107
## 132 NA 1.8540127 95.00000 7.898095
## 133 0.0707800 0.9234000 99.00000 7.983333
## 134 0.1280000 3.5051333 NA 7.958889
## 135 NA NA NA 7.960000
## 136 NA 1.6654640 95.22222 7.934524
## 137 NA NA NA 7.957143
## 138 0.1002000 0.6143330 103.33333 NA
## 139 0.1409000 3.2467945 90.57143 7.977614
## 140 NA NA NA 7.583333
## 141 0.1298000 3.1898820 81.85714 7.900000
## 142 NA 1.6913333 97.88889 8.115555
## 143 0.1499165 3.9136000 80.26667 7.900000
## 144 NA 2.5853223 NA 7.887778
## 145 0.0681670 1.4894290 103.07692 8.099231
## 146 NA 1.3283335 99.08333 8.058333
## 147 0.1202830 1.0670000 86.50000 7.916667
## 148 0.1280000 4.4750000 NA 8.000000
## 149 NA NA NA 7.200000
## 150 NA 1.2815000 NA 7.800000
## 151 NA 2.4628330 90.13889 8.016666
## 152 NA 5.2437777 67.87037 7.798809
## 153 NA 5.7014290 86.85714 7.942857
## 154 NA 1.8800000 95.50000 8.100000
## 155 NA 2.0825000 94.25000 8.075000
## 156 NA 3.7161832 91.40000 7.999833
## 157 0.1396670 4.6550000 NA 8.200000
## 158 NA NA NA 7.966667
## 159 0.1269670 NA NA 8.050000
## 160 NA 2.5810000 77.97500 7.902500
## 161 NA 2.7999525 97.37500 8.065238
## 162 NA NA NA 7.585714
## 163 NA 4.7900000 72.83333 7.862500
## 164 0.1143330 3.1733330 106.16667 8.083333
## 165 NA NA NA 7.620000
## 166 0.0854290 1.1739170 99.00000 8.125000
## 167 NA 1.9136983 98.54444 8.064286
## 168 NA 4.2135000 104.20000 8.141667
## 169 0.1553330 3.9352670 81.33333 7.906250
## 170 NA 5.1576667 66.79630 7.794643
## 171 NA NA NA 7.833333
## 172 NA 2.6722286 97.46667 8.068190
## 173 NA NA NA NA
## 174 NA 3.6016800 92.58667 8.012533
## 175 0.0978330 1.9724620 96.33333 8.036364
## 176 0.1388000 2.9401180 91.85714 7.994118
## 177 0.0158330 0.1580000 107.16667 8.250000
## 178 0.0073330 0.0316670 97.66667 8.195000
## 179 0.0081140 0.0490000 98.85714 8.185714
## 180 0.0249710 0.0800000 98.85714 8.214286
## 181 NA 0.2380000 NA 8.000000
## 182 NA 0.1500000 NA 7.956250
## 183 0.0080670 0.0450000 95.90000 8.063333
## 184 0.0185000 0.1575000 100.00000 8.350000
## 185 NA 0.3700000 NA 8.083333
## 186 0.0274290 0.1972860 99.00000 7.928571
## 187 0.0168330 0.1563330 97.50000 8.383333
## 188 0.0201670 0.2015000 103.16667 8.125000
## 189 NA 0.1390910 NA 7.990909
## 190 0.0169000 0.0705000 93.16667 8.086667
## 191 0.0107830 0.0640000 98.83333 8.200000
## 192 0.0088200 0.0415000 100.00000 8.020000
## 193 NA 0.0850000 NA 8.016666
## 194 NA 0.1652000 NA 8.150000
## 195 0.0131600 0.0536670 91.33333 8.080000
## 196 0.0167330 0.0300000 95.80000 8.100000
## 197 NA 0.1633330 NA 7.923077
## 198 NA 0.1600000 NA 8.225000
## 199 NA 0.1225000 NA 8.134615
## 200 0.0116000 0.0888570 96.14286 8.085714
## 201 NA 0.1033330 NA 8.007143
## 202 NA 0.1386000 NA 8.045455
## 203 0.0210000 0.1641670 102.16667 8.016667
## 204 0.0280000 0.2090000 94.75000 7.958333
## 205 0.0108330 0.1070000 98.83333 8.000000
## 206 NA 0.1160000 NA 8.066667
## 207 0.0160000 0.1904290 98.50000 8.071429
## 208 0.0114170 0.0456670 98.66667 8.150000
## 209 0.0327140 0.3107690 104.15385 8.112500
## 210 0.0095330 0.0328000 97.00000 8.032000
## 211 NA 0.3500000 NA 8.116667
## 212 0.0144290 0.0542860 97.00000 8.142857
## 213 NA 0.2020000 NA 7.911111
## 214 0.0109930 0.0692670 106.16667 8.200000
## 215 0.0183600 0.0850000 101.70000 8.118333
## 216 NA NA NA NA
## 217 NA 0.1500000 NA 7.881818
## 218 NA NA NA 8.266667
## 219 NA 0.0800000 NA 7.900000
## 220 NA 0.2900000 NA 8.020000
## 221 NA NA NA 8.100000
## 222 NA NA NA NA
## 223 0.0125000 0.1086670 107.50000 7.750000
## 224 0.0084430 0.0396670 97.43333 8.073750
## 225 0.0172500 0.0592220 NA 7.944444
## 226 NA 0.3450000 NA 8.079166
## 227 NA 0.3400000 NA 8.140000
## 228 0.0195000 0.1390000 102.85714 8.057143
## 229 0.0085800 0.0255000 101.75000 8.085000
## 230 NA NA NA 8.200000
## 231 0.0180000 0.1711110 83.55556 7.976667
## 232 0.0123240 0.0958710 98.85714 8.242857
## 233 NA 0.0993850 NA 7.992857
## 234 0.0111330 0.0333330 99.33333 8.123333
## 235 NA 0.1580000 NA 8.025000
## 236 NA 0.1633330 NA 7.916667
## 237 0.0177140 0.1890000 96.15385 8.107692
## 238 0.0230000 0.1543080 NA 8.100000
## 239 0.0221800 0.0653330 98.20000 8.160000
## 240 NA 0.3016670 NA 8.053846
## 241 0.0118330 0.1146670 93.66667 8.060000
## 242 0.0125000 0.1547270 NA 8.036364
## 243 0.0194440 0.1942220 95.18182 8.033333
## 244 0.0146510 0.1472570 99.85714 8.171429
## 245 NA 0.0850000 NA 8.000000
## 246 NA NA NA 8.100000
## 247 0.0173330 0.2260830 98.33333 8.116667
## 248 0.0118330 0.0841670 98.50000 8.133333
## 249 NA NA NA 8.200000
## 250 0.0132860 0.0825710 96.87500 7.964286
## 251 NA 0.1742500 NA 8.122665
## 252 0.0114830 0.0450000 98.15000 8.145000
## 253 0.0274000 0.2291820 96.27273 7.983333
## 254 NA 0.0850000 NA 8.044444
## 255 NA 0.3025000 NA 8.078571
## 256 0.0094670 0.0406670 98.50000 8.133333
## 257 NA 0.2322000 NA 8.130000
## 258 0.0142500 0.0948750 94.11111 7.977778
## 259 NA 0.1624440 NA 8.155556
## 260 NA NA NA NA
## 261 NA NA NA NA
## 262 0.0156670 0.0433330 99.00000 8.076667
## 263 NA NA NA NA
## 264 0.0076670 0.0270000 96.80000 8.150000
## 265 NA NA NA NA
## 266 NA NA NA NA
## 267 NA NA 100.00000 7.700000
## 268 NA NA NA NA
## 269 NA NA NA 7.450000
## 270 NA NA NA NA
## 271 NA NA NA NA
## 272 0.0222500 0.1287500 100.70000 7.725000
## 273 NA NA 103.00000 8.066667
## 274 0.0188570 0.0572860 106.60000 8.200000
## 275 NA NA NA NA
## 276 NA NA NA 7.850000
## 277 0.0099200 0.0268000 112.57143 8.242857
## 278 NA NA NA NA
## 279 NA NA NA 8.225000
## 280 0.0192000 0.0382000 95.80000 7.680000
## 281 0.0094170 0.0213330 100.00000 8.050000
## 282 NA NA NA NA
## 283 NA NA NA NA
## 284 0.0131430 0.0360000 97.00000 7.625000
## 285 0.0154000 0.0382000 96.40000 7.980000
## 286 NA 0.0238000 107.00000 7.960000
## 287 NA NA NA NA
## 288 0.0160000 0.0550000 103.20000 8.000000
## 289 0.0160000 0.0438330 97.33333 7.916667
## 290 NA NA NA NA
## 291 NA NA NA NA
## 292 0.0158320 0.0201500 97.90909 7.927273
## 293 NA 0.0600000 96.00000 7.940000
## 294 0.0153330 0.0536670 99.83333 7.966667
## 295 0.0063540 0.0229430 100.50000 8.150000
## 296 NA NA NA NA
## 297 NA NA NA NA
## 298 NA 0.0286670 101.50000 7.750000
## 299 NA NA NA 7.733333
## 300 NA NA NA 7.900000
## 301 0.0156000 0.0454000 106.42857 8.228571
## 302 NA 0.0673330 100.16667 7.933333
## 303 NA NA NA NA
## 304 NA NA NA NA
## 305 0.0138330 0.0491670 103.00000 8.000000
## 306 NA NA NA NA
## 307 NA NA NA NA
## 308 0.0205000 0.0355000 96.12500 7.950000
## 309 NA 0.0410000 102.16667 8.016667
## 310 NA NA NA 8.000000
## 311 NA 1.1141430 102.19048 7.814286
## 312 NA 2.7277780 NA 7.741667
## 313 NA 2.5000000 96.60000 7.800000
## 314 NA 2.1377780 128.48276 8.065517
## 315 0.1410000 1.7500000 93.60000 7.825000
## 316 0.2007140 2.0071430 72.71429 7.300000
## 317 0.1834000 1.8720000 89.20000 7.820000
## 318 0.0470000 1.6208330 101.33333 7.783333
## 319 NA 1.6091360 NA 8.004348
## 320 0.1265000 1.9100000 106.83333 8.141667
## 321 NA 1.4870000 86.16667 7.650000
## 322 NA NA NA NA
## 323 0.1493330 1.1000000 99.50000 7.616667
## 324 NA NA NA NA
## 325 NA 1.1941920 NA 7.855556
## 326 0.1038000 2.2400000 101.60000 7.780000
## 327 NA 1.4728330 97.83333 7.860000
## 328 NA 2.3136840 NA 7.537500
## 329 NA 1.5686670 NA 7.750000
## 330 NA 2.3340000 115.00000 7.980000
## 331 NA 1.6028570 5.00000 7.485000
## 332 NA 1.2211200 NA 7.753571
## 333 NA 1.0682500 NA 7.696296
## 334 0.1907140 1.4695710 88.14286 8.000000
## 335 NA 1.0602000 86.80000 7.540000
## 336 NA 0.8995710 88.57143 7.733333
## 337 NA 2.1087860 NA 7.530526
## 338 0.0926000 0.9561430 85.28571 7.828571
## 339 0.0899710 NA 85.85714 7.985714
## 340 NA 2.0566670 NA 7.528571
## 341 NA NA NA NA
## 342 NA 1.8675000 93.16667 7.716667
## 343 0.2046670 1.7503330 74.33333 7.500000
## 344 NA 1.1130000 85.33333 7.583333
## 345 NA 1.1248060 NA 7.761290
## 346 0.1028000 1.4308000 71.80000 7.500000
## 347 0.0940000 0.5340000 97.00000 7.700000
## 348 NA 1.2688700 NA 7.786957
## 349 0.1611170 3.1816670 82.57143 7.757143
## 350 0.0897170 NA 96.50000 8.166667
## 351 0.1232330 0.9040000 90.50000 7.800000
## 352 NA NA NA NA
## 353 0.1370000 1.7614290 95.71429 7.828571
## 354 NA 1.9530000 7.40000 7.544554
## 355 0.1933330 3.1516670 82.33333 7.816667
## 356 0.1550000 1.3150000 92.42857 7.642857
## 357 0.1308570 1.7904290 75.14286 7.614286
## 358 NA 1.8716670 107.83333 7.833333
## 359 NA 2.2131580 NA 7.582609
## 360 0.1483330 1.9595000 79.50000 7.883333
## 361 NA 2.1399470 NA 7.527368
## 362 NA 1.2800770 NA 7.876923
## 363 NA 1.9530000 7.40000 7.544607
## 364 NA 2.9425000 NA 7.709091
## 365 0.1546670 2.4400000 77.00000 7.600000
## 366 NA 2.7052630 NA 7.660000
## 367 NA 2.2007690 NA 7.740000
## 368 NA NA NA NA
## 369 0.0893330 NA 89.00000 8.011667
## 370 NA 2.2860000 NA 7.654545
## 371 0.0296330 0.0553330 90.46667 7.843333
## 372 0.0206830 0.0305000 89.33333 7.716667
## 373 NA NA NA 7.470000
## 374 NA NA NA 7.500000
## 375 0.0241000 NA 89.66667 8.083333
## 376 0.0504000 0.0508180 94.81818 7.590909
## 377 NA 0.0500000 NA 7.277778
## 378 NA NA NA NA
## 379 NA NA NA 7.616667
## 380 0.0238800 0.0364000 89.60000 7.862000
## 381 0.0237830 0.0727670 89.50000 7.400000
## 382 0.0150570 0.0366000 89.71429 7.760000
## 383 NA NA NA 7.642857
## 384 NA 0.0500000 97.00000 7.540000
## 385 NA 0.0600000 NA 7.466667
## 386 NA NA NA 7.491667
## 387 0.0491670 0.0530000 91.28571 7.557143
## 388 0.0364330 0.0508330 88.66667 7.750000
## 389 0.0185140 0.0500000 95.85714 7.785714
## 390 0.0236830 NA 87.50000 8.000000
## 391 NA NA NA 7.488889
## 392 NA NA NA 7.533333
## 393 NA 0.0530000 93.14286 7.571429
## 394 0.0410000 0.3113570 91.07143 7.700000
## 395 NA NA NA 7.300000
## 396 NA NA NA 7.450000
## 397 0.0201600 0.0756000 100.44000 7.854000
## 398 NA NA NA 7.385714
## 399 NA 0.7650000 NA 7.455556
## 400 NA NA NA 7.437500
## 401 0.0150330 0.0358330 92.76667 7.651667
## 402 NA 0.0600000 NA 7.469048
## 403 NA NA NA 7.500000
## 404 0.0411670 0.3021540 82.25000 7.446154
## 405 0.0464830 0.0523830 95.33333 7.666667
## 406 0.0371670 0.0566670 68.71429 7.328571
## 407 0.0380000 0.2872860 90.42857 7.750000
## 408 NA NA NA 7.480000
## 409 0.0352500 0.3493640 96.09091 7.890909
## 410 0.0252860 0.2776430 91.42857 7.564286
## 411 NA 0.0696000 87.60000 7.440000
## 412 0.0278330 0.2249000 95.07000 7.654545
## 413 0.0238170 NA 88.33333 7.733333
## 414 0.0351430 0.2463330 89.25000 7.600000
## 415 0.0404830 0.0800000 88.16667 7.616667
## 416 NA NA NA 7.520000
## 417 NA NA NA 7.433333
## 418 0.0320570 0.0385710 99.28571 7.871429
## 419 0.0420000 0.0453640 95.00000 7.554545
## 420 NA NA NA 7.500000
## 421 0.0473750 0.0560000 89.52500 7.675000
## 422 0.0242500 0.2642670 90.86667 7.486667
## 423 0.0223830 NA 93.50000 7.783333
## 424 0.0169670 0.0403330 95.26667 7.806667
## 425 0.0348330 0.2762500 92.65454 7.566667
## 426 NA NA NA 7.614286
## 427 NA NA NA NA
## 428 0.0269000 0.0677140 90.35714 7.812857
## 429 0.0312400 0.0428000 81.70000 7.960000
## 430 0.0360000 0.3457690 90.61539 7.446154
## 431 0.0236170 0.0680000 90.83333 7.550000
## 432 0.0283330 0.0333330 94.66667 7.500000
## 433 NA NA NA 7.557143
## 434 NA NA NA 7.520000
## 435 NA NA NA 7.512500
## 436 0.0128400 0.0596000 93.00000 7.520000
## 437 0.0183290 0.0607140 93.45714 7.811429
## 438 0.0421500 0.0616670 91.50000 7.583333
## 439 NA 0.0651670 88.66667 7.450000
## 440 0.0424000 NA 87.00000 7.778571
## 441 0.0610000 0.0536670 90.16667 7.550000
## 442 NA NA NA 7.900000
## 443 NA NA NA NA
## 444 NA NA NA NA
## 445 0.0040000 0.0200000 96.66667 8.066667
## 446 NA NA NA NA
## 447 NA NA NA 7.733333
## 448 0.0045710 0.0317140 93.14286 7.871429
## 449 NA NA NA NA
## 450 0.0040000 0.0200000 100.11667 7.920000
## 451 NA 0.0200000 96.71429 7.800000
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## 1448 NA NA NA NA
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## 1468 0.0148570 0.0781430 96.28571 7.714286
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## 1495 NA NA NA NA
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## 1498 NA NA NA 7.777778
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## 1512 NA NA NA NA
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## 1514 NA NA NA NA
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## 1517 NA NA NA 8.000000
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## 1523 NA 0.0552860 137.57143 8.385714
## 1524 NA 0.0581670 98.83333 7.900000
## 1525 0.0260170 0.0348000 104.66667 8.116667
## 1526 NA NA NA NA
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## 1528 NA 0.0642500 98.25000 7.900000
## 1529 0.0672000 0.0800000 94.60000 7.920000
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## 1531 NA NA NA NA
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## 1533 NA NA NA 8.283333
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## 1536 NA 0.0720000 NA 7.400000
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## 1538 NA 0.0641670 NA 8.000000
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## 1541 NA 0.1000000 NA 8.220000
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## 1543 0.0252500 0.0450000 103.80000 7.940000
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## 1546 NA 0.1835000 NA 7.950000
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## 1548 NA 0.1000000 NA 8.200000
## 1549 NA NA NA NA
## 1550 NA NA NA NA
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## 1552 NA NA NA 8.500000
## 1553 NA NA NA 8.275000
## 1554 NA NA NA 8.011111
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## 1591 0.0040000 0.0270000 90.00000 7.662000
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## 1594 0.0041430 0.0284290 88.65714 7.694286
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## 1604 NA NA NA NA
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## 1607 NA 0.1000000 NA 7.833333
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## 1609 0.0044860 0.0251670 79.75714 7.637143
## 1610 0.0040000 0.0503330 91.33333 7.716667
## 1611 0.0070000 0.0662860 94.85714 7.585714
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## 1677 0.0296830 0.2078330 98.33333 8.100000
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## 1679 NA NA NA NA
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## 1690 NA NA NA NA
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## 1701 NA NA 99.40000 8.116667
## 1702 NA NA NA NA
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## 1706 0.0272670 0.1065000 91.66667 8.000000
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## 1711 NA NA NA NA
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## 1723 NA NA NA 7.850000
## 1724 NA NA NA 7.866667
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## 1726 NA NA NA 7.860000
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## 1728 NA NA NA 7.800000
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## 1738 NA NA NA 8.000000
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## 1743 NA NA NA 8.012500
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## 1790 NA NA NA 8.200000
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## 1828 0.0575830 0.3523330 86.58333 7.750000
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## 1847 0.0370000 0.1720000 NA 7.916667
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## 1849 NA NA NA 7.966667
## 1850 NA NA NA 8.000000
## 1851 0.0648170 0.2116670 91.66667 8.206667
## 1852 0.1055000 0.8590000 113.33333 8.583333
## 1853 0.1284290 1.0018330 77.00000 8.116667
## 1854 NA NA NA 8.020000
## 1855 NA NA NA 8.216667
## 1856 NA NA NA 8.475000
## 1857 NA 1.6500000 124.28571 8.671429
## 1858 NA NA NA 8.216667
## 1859 NA NA NA 7.900000
## 1860 NA NA NA 8.383333
## 1861 NA NA NA 8.475000
## 1862 0.0985670 0.2711670 92.50000 8.133333
## 1863 NA NA NA 7.860000
## 1864 NA NA NA 8.180000
## 1865 0.1470000 1.8020000 107.80000 8.660000
## 1866 NA 2.2600000 119.00000 8.300000
## 1867 NA NA NA 8.100000
## 1868 NA 0.9880000 NA 8.250000
## 1869 NA NA NA 8.528571
## 1870 0.0565500 0.2510000 88.25000 8.090000
## 1871 0.1038330 0.3346670 94.16667 8.300000
## 1872 NA NA NA 8.157143
## 1873 NA 2.3000000 97.16667 8.166667
## 1874 NA 1.5960000 88.75000 8.140000
## 1875 0.0991670 1.1200000 102.66667 8.216667
## 1876 0.1150600 0.3328000 95.20000 8.100000
## 1877 0.0800000 0.6334290 101.42857 8.081429
## 1878 NA NA NA 8.414286
## 1879 0.0729000 0.2653330 97.20000 8.200000
## 1880 NA 1.1244000 96.66667 8.100000
## 1881 0.0767000 0.3182000 96.33333 8.166667
## 1882 0.1540000 2.0020000 85.00000 8.440000
## 1883 0.1080000 1.8300000 108.60000 8.360000
## 1884 0.0897830 0.3666670 102.33333 8.383333
## 1885 NA NA NA 7.875000
## 1886 NA NA NA 8.200000
## 1887 NA 1.9716670 98.00000 8.316667
## 1888 NA NA NA 8.214286
## 1889 NA 1.4020000 NA 8.283333
## 1890 0.0578330 0.5045000 94.75000 8.362500
## 1891 NA NA NA 7.933333
## 1892 0.0674670 0.2685000 93.66667 8.216667
## 1893 NA NA NA 7.983333
## 1894 0.1076670 0.9160000 115.83333 8.416667
## 1895 NA 2.1683330 106.83333 8.433333
## 1896 0.0981670 0.9028330 97.83333 8.050000
## 1897 NA NA NA 8.120000
## 1898 0.0692170 0.2996670 102.16667 8.200000
## 1899 NA NA NA 7.966667
## 1900 NA NA NA 7.900000
## 1901 0.0670670 0.3188330 98.16667 8.250000
## 1902 0.0497000 0.2840000 96.00000 8.100000
## 1903 0.1440000 0.9225000 103.60000 8.228333
## 1904 NA NA NA 8.050000
## 1905 0.1060170 0.2716670 102.00000 8.266667
## 1906 NA NA NA 7.771429
## 1907 NA 0.1766000 96.60000 7.880000
## 1908 0.0251430 0.1760000 108.71429 7.928571
## 1909 0.0098830 NA 101.66667 8.216667
## 1910 NA 0.2175000 NA 7.910000
## 1911 0.0261670 NA NA 7.866667
## 1912 NA NA NA 7.950000
## 1913 NA NA NA 7.916667
## 1914 0.0105750 0.0415000 98.50000 7.875000
## 1915 NA NA NA 7.875000
## 1916 0.0083330 0.1240000 95.00000 8.000000
## 1917 NA NA NA 7.716667
## 1918 0.0097710 0.0385000 97.42857 8.000000
## 1919 0.0150000 NA 101.00000 7.733333
## 1920 NA NA NA 8.060000
## 1921 NA NA NA 7.725000
## 1922 NA NA NA 7.760000
## 1923 NA 0.4211430 96.00000 7.814286
## 1924 0.0123330 0.4570000 98.57143 7.971429
## 1925 0.0170000 0.2654000 98.60000 7.920000
## 1926 NA NA NA 7.978333
## 1927 NA NA NA 7.775000
## 1928 NA NA NA 7.987143
## 1929 NA NA NA 7.785714
## 1930 NA 0.1836000 85.00000 7.720000
## 1931 NA NA NA 7.760000
## 1932 0.0081240 0.0604500 99.87500 8.062500
## 1933 NA NA NA 7.980000
## 1934 NA NA NA 7.760000
## 1935 0.0261670 0.1931670 95.16667 7.916667
## 1936 NA 0.2033330 NA 7.942857
## 1937 NA NA NA 7.916667
## 1938 NA NA NA 8.020000
## 1939 0.0310000 NA NA 7.960000
## 1940 NA NA NA 7.975000
## 1941 NA 0.2441430 96.71429 7.950000
## 1942 0.0306670 NA NA 7.616667
## 1943 0.0323330 NA NA 7.966667
## 1944 0.0250000 0.1090000 93.00000 7.860000
## 1945 NA NA NA NA
## 1946 NA NA NA 8.048000
## 1947 NA NA NA 8.100000
## 1948 0.0100810 0.0666000 96.22222 8.000000
## 1949 NA 0.1560000 99.00000 7.760000
## 1950 0.0145800 NA 95.40000 8.000000
## 1951 NA NA NA NA
## 1952 0.0285000 0.3215000 96.71429 7.585714
## 1953 0.0260000 NA NA 7.742857
## 1954 NA NA NA 7.950000
## 1955 NA NA NA 7.925000
## 1956 NA NA NA NA
## 1957 NA NA NA 7.757143
## 1958 0.0178330 0.2240000 88.16667 7.918182
## 1959 0.0171670 0.2145000 104.00000 7.980000
## 1960 0.0690000 0.2315710 98.28571 7.714286
## 1961 0.0393330 0.2363330 101.83333 7.550000
## 1962 NA NA 72.00000 8.044444
## 1963 NA 0.1588570 80.33333 8.085714
## 1964 NA NA NA 7.985714
## 1965 NA NA NA 8.128571
## 1966 0.0371710 0.2082860 95.57143 8.028571
## 1967 NA 0.1522860 87.57143 8.100000
## 1968 0.0559430 0.1852860 97.28571 8.000000
## 1969 NA NA NA 7.975000
## 1970 0.0447330 0.0876670 94.66667 8.043333
## 1971 NA NA NA 8.175000
## 1972 0.0341430 0.0730000 91.57143 7.888571
## 1973 NA NA NA 8.250000
## 1974 0.0360200 0.1112000 97.20000 7.880000
## 1975 0.0443670 0.0728330 95.66667 7.976667
## 1976 0.0376330 0.0312000 101.57143 8.015000
## 1977 NA NA NA 8.060000
## 1978 NA NA NA 7.971429
## 1979 NA 0.3930000 114.66667 8.133333
## 1980 NA NA NA 8.110000
## 1981 NA NA NA 8.233333
## 1982 NA NA NA 7.850000
## 1983 NA NA NA 7.900000
## 1984 NA 0.3646000 94.20000 8.060000
## 1985 NA NA NA 7.766667
## 1986 NA NA NA NA
## 1987 0.0604290 0.2431430 102.85714 8.200000
## 1988 0.0493670 0.0496670 102.50000 7.995000
## 1989 NA 0.2625000 90.37500 8.137500
## 1990 NA 0.2696670 98.50000 8.000000
## 1991 0.1374000 0.2544000 94.80000 7.780000
## 1992 0.0246670 0.1838000 99.20000 7.580000
## 1993 NA NA NA 8.133333
## 1994 NA 0.3940000 NA 8.100000
## 1995 0.0394330 0.0448330 97.83333 7.883333
## 1996 0.0273000 0.0750000 88.60000 8.010000
## 1997 NA 0.0926000 123.40000 8.160000
## 1998 0.0576000 0.0695000 99.35000 8.083333
## 1999 0.0445170 0.1010170 98.50000 7.933333
## 2000 NA 0.4248330 101.66667 8.083333
## 2001 NA NA NA 7.833333
## 2002 NA NA NA 7.820000
## 2003 NA NA NA 8.050000
## 2004 NA 0.3775000 99.00000 8.016667
## 2005 NA NA NA 7.916667
## 2006 0.0886000 0.2125000 96.66667 7.950000
## 2007 NA NA NA 8.071429
## 2008 0.0478830 0.0701670 93.83333 7.933333
## 2009 NA NA NA 7.830000
## 2010 NA NA NA 7.885714
## 2011 NA NA NA 7.983333
## 2012 0.0500000 0.3482000 91.33333 8.066667
## 2013 0.0778000 0.2688000 93.60000 7.700000
## 2014 NA NA NA 8.083333
## 2015 NA 0.3046670 90.33333 8.016667
## 2016 NA 0.1358570 86.85714 8.071429
## 2017 NA NA NA NA
## 2018 NA 0.2476250 101.50000 7.800000
## 2019 0.1120000 1.2240000 NA 7.880000
## 2020 0.0528330 0.3743330 93.50000 7.916667
## 2021 0.0275000 0.8928000 101.00000 8.240000
## 2022 0.0785000 2.9285710 NA 7.985714
## 2023 0.1094000 1.2500000 NA 7.858333
## 2024 NA 2.2678330 90.00000 7.916667
## 2025 0.0558830 0.3923330 89.93333 7.986667
## 2026 0.1220000 1.6740000 NA 7.980000
## 2027 0.0546670 1.3080000 114.18182 8.316667
## 2028 0.0296330 0.6690000 98.16667 8.266667
## 2029 0.0502500 0.5336670 96.33333 8.116667
## 2030 0.0861670 0.9716670 NA 7.957143
## 2031 0.0410000 1.0923330 92.25000 8.100000
## 2032 0.0310000 1.4638330 95.00000 8.100000
## 2033 0.0612860 0.7385710 96.55556 7.844444
## 2034 0.0764290 2.9407140 NA 8.185714
## 2035 0.0992500 1.2104170 NA 7.983333
## 2036 0.0588330 0.7836670 92.26667 8.040000
## 2037 0.0651110 0.2770000 NA 8.100000
## 2038 0.0930000 0.3738000 87.83333 7.920000
## 2039 0.0777000 0.7841000 NA 8.075000
## 2040 0.1008330 1.0916670 NA 7.969231
## 2041 NA 2.0666670 107.83333 8.300000
## 2042 0.0361430 0.3966670 93.71429 8.097143
## 2043 0.0258670 0.6120000 95.50000 8.133333
## 2044 0.0710000 1.7828570 NA 7.980000
## 2045 0.0651110 0.2770000 NA 8.100000
## 2046 0.0545000 1.2516670 94.00000 8.300000
## 2047 0.1103330 0.7800000 NA 7.942857
## 2048 0.0886670 0.7850000 NA 7.763636
## 2049 0.1014290 2.5685710 NA 8.057143
## 2050 0.0385800 0.2185000 88.80000 8.064000
## 2051 0.0417600 0.3548000 101.80000 8.000000
## 2052 0.0751500 0.9035000 NA 8.010000
## 2053 0.0726670 1.7916670 NA 7.866667
## 2054 0.0410710 0.4917500 91.00000 8.157143
## 2055 0.0633330 1.8958330 NA 8.041667
## 2056 0.0776470 1.1717650 NA 8.170588
## 2057 0.0791670 0.5661430 113.00000 8.148571
## 2058 0.0518170 0.5561670 97.16667 8.066667
## 2059 0.0498830 0.1878000 81.83333 7.921667
## 2060 0.0590830 0.5145000 NA 8.176923
## 2061 0.0525710 0.7355710 81.00000 7.928571
## 2062 0.0875000 0.6386000 88.40000 7.900000
## 2063 0.0710000 0.6858000 92.20000 7.820000
## 2064 0.0323140 0.2981430 92.14286 7.942857
## 2065 NA 1.1534000 109.66667 8.040000
## 2066 0.0307200 0.1166000 94.40000 7.980000
## 2067 NA 2.7314290 109.00000 8.128571
## 2068 0.0551670 0.7391670 94.33333 8.166667
## 2069 0.0541430 0.4292860 98.14286 8.128571
## 2070 0.0325800 0.3410000 80.80000 7.780000
## 2071 NA 0.9431670 94.83333 7.900000
## 2072 0.0666670 1.6609090 NA 8.254545
## 2073 0.0210750 0.1342500 98.42500 8.295000
## 2074 0.0850000 2.3462500 NA 7.975000
## 2075 0.0600000 1.3954550 NA 8.254545
## 2076 0.0660670 1.4903330 NA 8.266667
## 2077 NA NA NA 8.111111
## 2078 NA 0.4021670 93.00000 7.966667
## 2079 NA NA NA 8.133333
## 2080 NA NA NA 8.116667
## 2081 NA NA NA 8.109091
## 2082 NA NA NA 7.900000
## 2083 NA NA NA 8.111111
## 2084 NA NA NA 7.916667
## 2085 NA NA NA 7.950000
## 2086 NA NA NA 7.950000
## 2087 NA NA NA 7.783333
## 2088 0.0361670 0.2151670 102.16667 8.066667
## 2089 NA NA NA 8.128571
## 2090 NA NA NA 7.962500
## 2091 NA NA NA 8.242857
## 2092 NA 0.3677140 77.00000 7.925714
## 2093 0.0307830 0.0920000 98.93333 8.080000
## 2094 NA NA NA NA
## 2095 0.0570000 NA NA 8.116667
## 2096 0.0192330 0.1690000 109.60000 8.183333
## 2097 0.0262830 0.1735000 97.66667 8.066667
## 2098 NA NA NA 8.166667
## 2099 0.0183600 0.1400000 97.60000 8.198000
## 2100 0.0201670 0.2675000 93.30000 8.053333
## 2101 0.0229830 0.0783330 97.83333 7.930000
## 2102 NA NA 101.40000 8.140000
## 2103 NA 0.5285710 102.28571 8.185714
## 2104 NA NA NA 8.100000
## 2105 NA NA NA 8.112500
## 2106 NA NA NA 7.850000
## 2107 NA NA NA 7.914286
## 2108 0.0294670 0.1040000 107.00000 8.156667
## 2109 NA NA NA 8.063750
## 2110 0.0645000 NA 94.75000 7.837500
## 2111 NA NA NA 8.091667
## 2112 0.0405000 0.4206670 101.28571 8.100000
## 2113 0.0301430 0.2928570 95.00000 7.871429
## 2114 NA NA NA 7.750000
## 2115 NA 1.0871670 101.33333 8.116667
## 2116 0.0197830 0.0910000 97.00000 8.086667
## 2117 NA NA NA 7.966667
## 2118 NA NA NA 8.037500
## 2119 NA NA NA 8.044444
## 2120 NA NA NA 8.180000
## 2121 NA NA NA 8.000000
## 2122 NA 0.4815000 91.50000 8.250000
## 2123 0.0320000 0.1940000 96.00000 8.000000
## 2124 NA NA NA 7.800000
## 2125 NA NA NA NA
## 2126 0.0271830 0.2021670 98.83333 8.083333
## 2127 0.1216670 1.1003330 87.14286 8.257143
## 2128 0.0586330 0.2855000 84.81667 8.076667
## 2129 0.0830000 0.3053330 75.16667 7.933333
## 2130 0.0605670 0.1965000 89.16667 8.065000
## 2131 0.1131430 0.9158570 79.57143 7.942857
## 2132 NA 2.1023080 NA 7.992000
## 2133 NA 1.6196670 NA 8.056667
## 2134 NA 2.2633330 NA 8.376923
## 2135 NA 1.5660000 NA 8.007407
## 2136 0.1400000 2.8250000 NA 7.845455
## 2137 0.1362500 1.7077780 NA 8.230769
## 2138 NA 2.1112500 NA 8.485714
## 2139 0.0558500 0.3893330 78.16667 7.958333
## 2140 NA NA NA NA
## 2141 0.0682200 0.3030000 101.00000 8.400000
## 2142 0.0883700 0.2633000 96.91667 8.150000
## 2143 0.1273330 2.0842860 106.08333 8.463636
## 2144 NA 1.9272220 NA 7.819231
## 2145 NA 1.6915380 NA 8.095455
## 2146 0.0972000 1.9360000 86.40000 8.271429
## 2147 0.1265000 1.9750000 107.37500 8.125000
## 2148 0.3000000 1.5750000 NA 7.625000
## 2149 0.1133080 1.0807060 NA 8.205263
## 2150 0.1937500 2.0433330 NA 8.186087
## 2151 0.0597600 0.3214000 94.58000 8.194000
## 2152 0.0947140 0.6040000 98.33333 8.300000
## 2153 0.0841330 0.2851670 83.00000 7.457143
## 2154 NA 2.2964290 NA 7.977273
## 2155 0.1271430 2.4136000 93.29412 8.006250
## 2156 0.0992000 1.6600000 81.22222 8.100000
## 2157 0.0925000 1.3975000 104.25000 8.050000
## 2158 0.0671830 0.2591670 94.77778 8.133333
## 2159 0.0666000 0.3485710 68.00000 7.828571
## 2160 0.1081250 0.7818750 92.33333 7.988889
## 2161 0.0723860 0.2257140 94.57143 8.014286
## 2162 0.0849670 0.3166670 83.33333 8.016667
## 2163 NA 1.9540000 NA 7.965000
## 2164 NA 2.5088240 NA 8.300000
## 2165 0.0664670 0.2765000 76.66667 8.150000
## 2166 0.1192000 1.1582860 95.03333 8.025000
## 2167 0.0909200 0.2926000 87.00000 7.962500
## 2168 0.1004290 2.0854550 85.36364 8.381818
## 2169 0.0830000 1.8866670 106.20000 8.250000
## 2170 0.0852430 0.4000000 105.77778 8.522222
## 2171 NA 1.9869230 NA 7.789655
## 2172 0.1202500 1.0628890 NA 8.004348
## 2173 0.1171430 2.0453850 88.23077 8.191667
## 2174 0.2200000 1.9111110 NA 7.906154
## 2175 NA 2.3122220 NA 8.210000
## 2176 0.0919330 0.2350000 61.33333 7.816667
## 2177 0.1841880 1.5950000 NA 8.266667
## 2178 0.0730000 0.6145000 91.00000 8.228571
## 2179 NA 1.5741670 NA 7.848000
## 2180 0.1150000 0.4510000 76.80000 8.040000
## 2181 NA 2.0675000 NA 8.040000
## 2182 0.0762860 0.9062860 99.62500 8.412500
## 2183 0.1448570 3.0135710 101.12500 8.306250
## 2184 0.0769170 0.3338330 84.25000 8.036667
## 2185 0.0833330 1.0996670 92.14286 7.957143
## 2186 NA 1.8580000 NA 7.929412
## 2187 0.0635860 0.2340000 93.30000 8.070000
## 2188 0.0636830 0.2696670 96.33333 8.300000
## 2189 NA 2.7468750 NA 8.081481
## 2190 NA 2.5883330 NA 7.969565
## 2191 0.0641860 0.3505710 99.85714 8.300000
## 2192 0.0848500 0.2696670 86.50000 7.980000
## 2193 0.0642500 0.2791670 94.50000 8.200000
## 2194 0.1240000 2.0876920 108.14286 8.335714
## 2195 0.2300000 1.9900000 NA 8.180952
## 2196 0.0672500 0.3283330 93.51667 8.131667
## 2197 NA 2.5966670 NA 8.277273
## 2198 0.0573670 0.3051670 94.83333 8.050000
## 2199 0.1305000 1.3650000 92.00000 8.433333
## 2200 0.0766670 1.9783330 91.57143 7.977143
## 2201 0.0700000 0.9556670 100.33333 8.083333
## 2202 NA 2.3750000 NA 7.968182
## 2203 NA 3.0666670 NA 7.981818
## 2204 NA 2.1691670 NA 8.075000
## 2205 NA NA NA 7.850000
## 2206 NA 2.1000000 NA 7.831818
## 2207 0.0563000 0.6300000 96.15000 7.882857
## 2208 NA NA NA 7.858333
## 2209 NA NA NA NA
## 2210 NA 3.0183330 NA 7.800000
## 2211 0.0526330 0.7475000 93.00000 7.955000
## 2212 NA 1.5643330 109.33333 7.800000
## 2213 NA 2.9500000 NA 7.834615
## 2214 0.0845000 2.2493330 90.83333 7.766667
## 2215 0.0802000 0.7014000 99.20000 7.500000
## 2216 0.0555370 NA 92.50000 7.875000
## 2217 NA 3.1005000 96.37500 8.000000
## 2218 NA 3.0300000 NA 7.778571
## 2219 NA 1.8180000 NA 7.800000
## 2220 NA 2.9842860 94.16667 8.066667
## 2221 0.0506400 0.2256670 90.80000 7.840000
## 2222 NA 2.9328570 NA 7.773333
## 2223 0.0437500 0.7910000 93.80000 7.901429
## 2224 NA 2.1525000 NA 7.670000
## 2225 0.0383670 0.2435000 94.50000 7.825000
## 2226 NA 3.2616670 93.08333 8.050000
## 2227 0.0469000 0.4180000 93.00000 7.860000
## 2228 NA 1.4127140 NA 7.873333
## 2229 NA 2.5126920 83.46154 7.915385
## 2230 NA 2.7533330 89.90000 7.960000
## 2231 NA 2.1400000 NA 7.963636
## 2232 0.0558870 1.8526250 89.62500 7.925000
## 2233 0.0602000 0.8500000 88.50000 7.880000
## 2234 NA 4.0000000 NA 7.850000
## 2235 NA 2.6580000 NA 7.888889
## 2236 0.0504400 NA 93.20000 7.840000
## 2237 0.0495000 0.7235000 88.50000 7.916667
## 2238 NA 5.5250000 NA 7.892105
## 2239 NA 3.0250000 NA 7.842857
## 2240 NA 2.0140000 NA 7.954545
## 2241 0.0481170 0.3750000 98.00000 7.821667
## 2242 NA 1.5600000 NA 7.954545
## 2243 NA 2.1975000 NA 7.933333
## 2244 NA 0.8324000 NA 7.741667
## 2245 0.0303170 NA 94.50000 7.800000
## 2246 NA NA NA 7.923333
## 2247 0.0395710 0.5115710 92.00000 7.871429
## 2248 NA 3.8638570 95.57143 7.994118
## 2249 0.0781000 1.1975710 92.71429 7.742857
## 2250 0.0419500 0.3833330 97.66667 7.933333
## 2251 NA 2.0616670 NA 7.936364
## 2252 0.0334000 0.3965000 92.65000 7.865000
## 2253 NA 1.5370000 92.60000 7.860000
## 2254 NA 4.2833330 NA 7.876667
## 2255 NA 3.9000000 NA 7.969231
## 2256 NA 2.5250000 NA 7.956591
## 2257 0.0407000 0.9100000 91.15000 7.968333
## 2258 NA 3.8500000 NA 7.886667
## 2259 NA 4.7500000 80.00000 7.900000
## 2260 NA 0.9598000 96.66667 7.770000
## 2261 NA 1.3072860 NA 7.876923
## 2262 NA NA NA 7.850000
## 2263 NA 2.1340000 NA 7.800000
## 2264 NA NA NA 7.877778
## 2265 NA NA NA NA
## 2266 NA 2.9328570 NA 7.767917
## 2267 NA 2.9926000 89.80000 8.018182
## 2268 NA 3.1760000 85.20000 7.900000
## 2269 NA NA NA 7.971429
## 2270 NA NA NA 7.940000
## 2271 0.0746670 0.6006670 87.50000 7.683333
## 2272 NA NA NA 8.000000
## 2273 NA NA NA 7.650000
## 2274 0.0172000 0.0983330 90.83333 7.683333
## 2275 0.0164980 0.4370000 90.00000 7.760000
## 2276 NA NA NA 7.920000
## 2277 NA 2.9200000 94.33333 7.900000
## 2278 NA 1.2133330 88.50000 7.750000
## 2279 0.0220000 0.4145000 89.16667 7.833333
## 2280 NA NA NA 7.683333
## 2281 0.0560000 0.6478330 92.80000 7.800000
## 2282 NA NA NA 8.016667
## 2283 NA NA NA 7.710000
## 2284 NA NA 99.00000 7.816667
## 2285 NA 0.6843330 87.00000 7.833333
## 2286 0.0221430 0.4968570 84.85714 7.742857
## 2287 NA NA NA 7.890000
## 2288 0.0195670 0.0975000 90.00000 7.850000
## 2289 NA NA NA 7.822222
## 2290 NA NA NA 7.670000
## 2291 NA NA NA 7.675000
## 2292 NA NA NA 7.816667
## 2293 NA NA NA 7.828571
## 2294 NA 0.4405000 101.75000 7.900000
## 2295 0.0138400 0.0632000 92.20000 7.828000
## 2296 NA NA NA 7.937500
## 2297 NA NA NA 7.700000
## 2298 NA NA NA 7.900000
## 2299 NA NA NA 8.070000
## 2300 NA 0.7618330 85.50000 7.666667
## 2301 NA NA NA 7.885714
## 2302 0.0172930 0.2568570 89.71429 7.685714
## 2303 NA 0.4416670 87.33333 7.616667
## 2304 NA 0.3698330 89.83333 7.700000
## 2305 0.0275000 1.0718330 84.33333 8.066667
## 2306 0.0142500 0.0655000 87.33333 7.816667
## 2307 0.0160000 0.0420000 89.85000 7.680000
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## 1937 NA NA NA
## 1938 NA NA NA
## 1939 NA NA NA
## 1940 NA NA NA
## 1941 NA NA NA
## 1942 NA NA NA
## 1943 NA NA NA
## 1944 NA NA NA
## 1945 NA NA NA
## 1946 NA NA NA
## 1947 NA NA NA
## 1948 NA NA NA
## 1949 NA NA NA
## 1950 NA 0.013000000 NA
## 1951 NA NA NA
## 1952 NA NA NA
## 1953 NA NA NA
## 1954 NA NA NA
## 1955 NA NA NA
## 1956 NA 0.013000000 NA
## 1957 NA NA NA
## 1958 NA NA NA
## 1959 NA NA NA
## 1960 NA NA NA
## 1961 NA NA NA
## 1962 NA NA NA
## 1963 NA NA NA
## 1964 NA NA NA
## 1965 NA NA NA
## 1966 NA NA NA
## 1967 NA NA NA
## 1968 NA NA NA
## 1969 NA NA NA
## 1970 NA 0.013000000 NA
## 1971 NA NA NA
## 1972 NA NA NA
## 1973 NA NA NA
## 1974 NA NA NA
## 1975 NA 0.013000000 NA
## 1976 NA NA NA
## 1977 NA NA NA
## 1978 NA NA NA
## 1979 NA NA NA
## 1980 NA NA NA
## 1981 NA NA NA
## 1982 NA NA NA
## 1983 NA NA NA
## 1984 NA NA NA
## 1985 NA NA NA
## 1986 NA NA NA
## 1987 NA NA NA
## 1988 NA NA NA
## 1989 NA NA NA
## 1990 NA NA NA
## 1991 NA NA NA
## 1992 NA NA NA
## 1993 NA NA NA
## 1994 NA NA NA
## 1995 NA NA NA
## 1996 NA NA NA
## 1997 NA NA NA
## 1998 NA NA NA
## 1999 NA NA NA
## 2000 NA NA NA
## 2001 NA NA NA
## 2002 NA NA NA
## 2003 NA NA NA
## 2004 NA NA NA
## 2005 NA NA NA
## 2006 NA NA NA
## 2007 NA NA NA
## 2008 NA NA NA
## 2009 NA NA NA
## 2010 NA NA NA
## 2011 NA NA NA
## 2012 NA NA NA
## 2013 NA NA NA
## 2014 NA NA NA
## 2015 NA NA NA
## 2016 NA NA NA
## 2017 NA 0.013000000 NA
## 2018 NA NA NA
## 2019 NA NA NA
## 2020 NA 0.016510000 NA
## 2021 NA NA NA
## 2022 NA NA NA
## 2023 NA NA NA
## 2024 NA NA NA
## 2025 NA NA NA
## 2026 NA NA NA
## 2027 NA NA NA
## 2028 NA NA NA
## 2029 NA NA NA
## 2030 NA NA NA
## 2031 NA NA NA
## 2032 NA NA NA
## 2033 NA 0.609200000 NA
## 2034 NA NA NA
## 2035 NA NA NA
## 2036 NA NA NA
## 2037 NA NA NA
## 2038 NA NA NA
## 2039 NA NA NA
## 2040 NA NA NA
## 2041 NA NA NA
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## 2120 NA NA NA
## 2121 NA NA NA
## 2122 NA NA NA
## 2123 NA NA NA
## 2124 NA NA NA
## 2125 NA NA NA
## 2126 NA NA NA
## 2127 0.1000000 0.010000000 NA
## 2128 NA NA NA
## 2129 0.0200000 0.013000000 NA
## 2130 NA 0.013000000 NA
## 2131 0.1000000 0.003000000 NA
## 2132 NA NA NA
## 2133 NA NA NA
## 2134 NA NA NA
## 2135 NA NA NA
## 2136 NA NA NA
## 2137 NA NA NA
## 2138 NA NA NA
## 2139 NA NA NA
## 2140 NA NA NA
## 2141 0.0200000 0.013000000 NA
## 2142 0.1000000 0.004000000 NA
## 2143 NA NA NA
## 2144 NA NA NA
## 2145 NA NA NA
## 2146 0.1000000 0.010000000 NA
## 2147 NA NA NA
## 2148 NA NA NA
## 2149 NA NA NA
## 2150 NA NA NA
## 2151 0.0200000 0.013000000 NA
## 2152 0.1000000 0.010000000 NA
## 2153 NA NA NA
## 2154 NA NA NA
## 2155 NA NA NA
## 2156 NA NA NA
## 2157 0.1000000 0.003000000 NA
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## 2159 0.0200000 0.013000000 NA
## 2160 0.1000000 0.010000000 NA
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## 2163 NA NA NA
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## 2165 0.0200000 0.013000000 NA
## 2166 NA NA NA
## 2167 0.1000000 0.004000000 NA
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## 2169 0.1000000 0.010000000 NA
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## 2172 NA NA NA
## 2173 NA NA NA
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## 2175 NA NA NA
## 2176 0.0200000 0.013000000 NA
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## 2178 0.1000000 0.010000000 NA
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## 2180 NA NA NA
## 2181 NA NA NA
## 2182 0.1000000 0.010000000 NA
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## 2184 NA NA NA
## 2185 NA NA NA
## 2186 NA NA NA
## 2187 0.0200000 0.004000000 NA
## 2188 0.0200000 0.010000000 NA
## 2189 NA NA NA
## 2190 NA NA NA
## 2191 0.1000000 0.010000000 NA
## 2192 0.0200000 0.010000000 NA
## 2193 0.0200000 0.013000000 NA
## 2194 NA NA NA
## 2195 NA NA NA
## 2196 NA NA NA
## 2197 NA NA NA
## 2198 0.0200000 0.010000000 NA
## 2199 0.1000000 0.003000000 NA
## 2200 0.1000000 0.003000000 NA
## 2201 0.1000000 0.003000000 NA
## 2202 NA NA NA
## 2203 NA NA NA
## 2204 NA NA NA
## 2205 NA NA NA
## 2206 NA NA NA
## 2207 0.0200000 0.013000000 NA
## 2208 NA NA NA
## 2209 0.0200000 0.013000000 NA
## 2210 NA NA NA
## 2211 0.0200000 0.005000000 NA
## 2212 NA NA NA
## 2213 NA NA NA
## 2214 0.1000000 0.003000000 NA
## 2215 0.1000000 0.003000000 NA
## 2216 NA NA NA
## 2217 NA NA NA
## 2218 NA NA NA
## 2219 NA NA NA
## 2220 NA NA NA
## 2221 0.0200000 0.010000000 NA
## 2222 NA NA NA
## 2223 0.0200000 0.013000000 NA
## 2224 NA NA NA
## 2225 0.0200000 0.005000000 NA
## 2226 NA NA NA
## 2227 0.0200000 0.013000000 NA
## 2228 NA NA NA
## 2229 NA NA NA
## 2230 NA NA NA
## 2231 NA NA NA
## 2232 0.1333333 0.003250000 NA
## 2233 0.0200000 0.013000000 NA
## 2234 NA NA NA
## 2235 NA NA NA
## 2236 0.0200000 0.005000000 NA
## 2237 0.0200000 0.005000000 NA
## 2238 NA NA NA
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## 2241 0.0200000 0.005000000 NA
## 2242 NA NA NA
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## 2244 NA NA NA
## 2245 NA NA NA
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## 2247 0.0200000 0.010000000 NA
## 2248 NA 0.220000000 NA
## 2249 0.1000000 0.003000000 NA
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## 2252 0.0200000 0.013000000 NA
## 2253 0.1000000 0.010000000 NA
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## 2255 NA NA NA
## 2256 NA NA NA
## 2257 0.0200000 0.006505000 NA
## 2258 NA NA NA
## 2259 NA NA NA
## 2260 NA NA NA
## 2261 NA NA NA
## 2262 NA NA NA
## 2263 NA NA NA
## 2264 NA NA NA
## 2265 0.0200000 0.013000000 NA
## 2266 NA NA NA
## 2267 NA NA NA
## 2268 0.1000000 0.003000000 NA
## 2269 NA NA NA
## 2270 NA NA NA
## 2271 NA NA NA
## 2272 NA NA NA
## 2273 NA NA NA
## 2274 NA NA NA
## 2275 NA NA NA
## 2276 NA NA NA
## 2277 NA NA NA
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## 2281 NA NA NA
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## 2285 NA NA NA
## 2286 NA NA NA
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## 2290 NA NA NA
## 2291 NA NA NA
## 2292 NA NA NA
## 2293 NA NA NA
## 2294 NA NA NA
## 2295 NA NA NA
## 2296 NA NA NA
## 2297 NA NA NA
## 2298 NA NA NA
## 2299 NA NA NA
## 2300 NA NA NA
## 2301 NA NA NA
## 2302 NA NA NA
## 2303 NA NA NA
## 2304 NA NA NA
## 2305 NA NA NA
## 2306 NA NA NA
## 2307 NA NA NA
## 2308 NA NA NA
## 2309 NA NA NA
## 2310 NA NA NA
## 2311 NA NA NA
## 2312 NA NA NA
## 2313 NA NA NA
## 2314 NA NA NA
## 2315 NA NA NA
## 2316 NA NA NA
## 2317 NA NA NA
## 2318 NA NA NA
## 2319 NA NA NA
## flow_mean temp_mean dates SITE_ID
## 1 89.1960970 13.067317 1992-09-01 47046
## 2 89.1960970 7.497844 2012-04-03 47046
## 3 89.1960970 14.564821 2016-11-03 47046
## 4 89.1960970 6.823230 1991-03-04 47046
## 5 89.1960970 6.637845 2013-03-04 47046
## 6 89.1960970 6.130656 2006-04-04 47046
## 7 89.1960970 12.743678 1991-09-04 47046
## 8 89.1960970 10.134330 1998-02-05 47046
## 9 89.1960970 12.864843 1994-09-05 47046
## 10 89.1960970 13.302398 1995-09-06 47046
## 11 89.1960970 12.625510 1986-10-06 47046
## 12 89.1960970 5.499816 2011-04-07 47046
## 13 89.1960970 13.940344 2013-10-07 47046
## 14 89.1960970 14.731059 1989-11-07 47046
## 15 89.1960970 12.019831 1987-09-08 47046
## 16 89.1960970 12.508915 1993-09-08 47046
## 17 89.1960970 6.237584 1994-03-09 47046
## 18 89.1960970 6.811000 2015-04-09 47046
## 19 89.1960970 6.786647 2002-05-09 47046
## 20 89.1960970 13.508399 1996-10-09 47046
## 21 89.1960970 13.514933 1998-10-09 47046
## 22 89.1960970 14.096341 2002-10-09 47046
## 23 89.1960970 14.204348 2005-10-10 47046
## 24 89.1960970 5.102146 1996-04-11 47046
## 25 89.1960970 5.602527 2001-05-11 47046
## 26 89.1960970 6.716104 2005-05-11 47046
## 27 89.1960970 5.232540 2010-05-11 47046
## 28 89.1960970 6.495616 1991-06-11 47046
## 29 89.1960970 14.405682 2011-10-11 47046
## 30 89.1960970 12.589858 2012-09-13 47046
## 31 89.1960970 8.201274 1990-03-14 47046
## 32 89.1960970 9.066972 1988-07-15 47046
## 33 89.1960970 14.285134 1997-10-16 47046
## 34 89.1960970 13.802300 1990-09-17 47046
## 35 89.1960970 14.319897 2017-11-17 47046
## 36 89.1960970 6.234567 2009-03-19 47046
## 37 89.1960970 12.304003 1985-09-19 47046
## 38 89.1960970 13.096755 2008-09-19 47046
## 39 89.1960970 7.430820 2000-03-20 47046
## 40 89.1960970 6.051079 1985-06-20 47046
## 41 89.1960970 8.607636 1989-02-21 47046
## 42 89.1960970 7.133346 1999-05-21 47046
## 43 89.1960970 14.117418 2010-10-21 47046
## 44 89.1960970 NA 2018-11-21 47046
## 45 89.1960970 5.607855 2011-03-22 47046
## 46 89.1960970 6.358958 2008-04-22 47046
## 47 89.1960970 6.880035 2003-05-22 47046
## 48 89.1960970 12.341594 1989-08-22 47046
## 49 89.1960970 7.205592 1995-03-23 47046
## 50 89.1960970 8.008376 2016-03-23 47046
## 51 89.1960970 5.258799 1987-04-23 47046
## 52 89.1960970 4.708796 2018-05-23 47046
## 53 89.1960970 6.000534 1986-06-23 47046
## 54 89.1960970 8.711817 1992-06-23 47046
## 55 89.1960970 7.583683 2017-05-25 47046
## 56 89.1960970 9.214149 1990-06-25 47046
## 57 89.1960970 7.958334 1988-02-26 47046
## 58 89.1960970 7.915004 1992-02-26 47046
## 59 89.1960970 13.362144 2015-10-26 47046
## 60 89.1960970 9.154951 1997-01-27 47046
## 61 89.1960970 5.541530 1985-03-27 47046
## 62 89.1960970 14.289105 2009-10-27 47046
## 63 89.1960970 5.131517 1986-03-28 47046
## 64 89.1960970 6.001474 1993-03-29 47046
## 65 89.1960970 14.684972 2003-09-29 47046
## 66 89.1960970 12.431713 1988-11-29 47046
## 67 89.1960970 5.532594 2011-03-31 47046
## 68 89.1960970 15.577226 2006-10-31 47046
## 69 89.1960970 14.596238 2014-10-31 47046
## 70 1.3464554 12.193162 1986-10-01 47078
## 71 1.3464554 6.807670 1995-05-02 47078
## 72 1.3464554 6.869494 1995-06-02 47078
## 73 1.3464554 5.688802 1993-04-03 47078
## 74 1.3464554 8.226097 1998-03-04 47078
## 75 1.3464554 7.238451 1995-04-04 47078
## 76 1.3464554 6.358787 1999-05-04 47078
## 77 1.3464554 12.179749 1985-12-04 47078
## 78 1.3464554 12.598207 1995-01-05 47078
## 79 1.3464554 13.517608 1994-12-05 47078
## 80 1.3464554 5.997962 1986-03-06 47078
## 81 1.3464554 14.768682 1995-11-06 47078
## 82 1.3464554 14.048336 2013-11-06 47078
## 83 1.3464554 10.432570 1995-02-07 47078
## 84 1.3464554 8.559216 1995-03-07 47078
## 85 1.3464554 6.374644 2008-05-07 47078
## 86 1.3464554 12.583186 1998-09-07 47078
## 87 1.3464554 8.141734 1998-03-08 47078
## 88 1.3464554 13.711938 1994-11-08 47078
## 89 1.3464554 8.918447 1999-02-09 47078
## 90 1.3464554 6.517183 2000-04-10 47078
## 91 1.3464554 14.018561 1990-10-10 47078
## 92 1.3464554 12.155814 1986-12-10 47078
## 93 1.3464554 11.497709 2001-01-11 47078
## 94 1.3464554 8.009520 1991-07-11 47078
## 95 1.3464554 13.580887 1995-09-11 47078
## 96 1.3464554 14.136196 1995-10-11 47078
## 97 1.3464554 8.042454 1998-03-12 47078
## 98 1.3464554 5.360071 1996-04-12 47078
## 99 1.3464554 6.614726 2005-04-12 47078
## 100 1.3464554 4.145248 1986-05-12 47078
## 101 1.3464554 6.923632 1998-05-12 47078
## 102 1.3464554 7.066163 1995-06-13 47078
## 103 1.3464554 10.102865 1987-08-13 47078
## 104 1.3464554 11.932648 1997-08-13 47078
## 105 1.3464554 13.257809 1989-09-13 47078
## 106 1.3464554 13.120041 2002-09-13 47078
## 107 1.3464554 4.687981 1996-05-14 47078
## 108 1.3464554 14.156697 1992-10-14 47078
## 109 1.3464554 5.922699 1988-04-15 47078
## 110 1.3464554 5.684554 1991-04-15 47078
## 111 1.3464554 14.557562 1989-11-15 47078
## 112 1.3464554 9.767309 1996-02-16 47078
## 113 1.3464554 6.328163 1999-04-16 47078
## 114 1.3464554 6.241593 2003-04-16 47078
## 115 1.3464554 4.957810 2013-05-16 47078
## 116 1.3464554 12.280081 1996-01-17 47078
## 117 1.3464554 5.719111 1985-06-17 47078
## 118 1.3464554 5.267959 1996-06-17 47078
## 119 1.3464554 12.115693 1999-08-17 47078
## 120 1.3464554 11.952419 1996-12-17 47078
## 121 1.3464554 5.206715 1994-04-18 47078
## 122 1.3464554 13.654705 1994-11-18 47078
## 123 1.3464554 7.107314 1996-03-19 47078
## 124 1.3464554 6.951334 1995-04-19 47078
## 125 1.3464554 6.780258 1995-05-19 47078
## 126 1.3464554 7.187669 1998-04-20 47078
## 127 1.3464554 7.483269 2014-05-20 47078
## 128 1.3464554 7.547702 2000-06-20 47078
## 129 1.3464554 9.808141 1993-07-20 47078
## 130 1.3464554 13.007866 1998-11-20 47078
## 131 1.3464554 13.817157 1995-12-20 47078
## 132 1.3464554 9.434619 1995-02-21 47078
## 133 1.3464554 13.255087 2008-11-21 47078
## 134 1.3464554 13.230641 1994-12-21 47078
## 135 1.3464554 8.026230 1988-02-22 47078
## 136 1.3464554 7.836018 1995-03-22 47078
## 137 1.3464554 7.055341 1989-05-22 47078
## 138 1.3464554 6.627760 2012-05-22 47078
## 139 1.3464554 11.102797 2000-08-22 47078
## 140 1.3464554 12.558666 1988-11-22 47078
## 141 1.3464554 12.104927 2000-12-22 47078
## 142 1.3464554 5.133168 1996-04-23 47078
## 143 1.3464554 13.592354 2000-10-23 47078
## 144 1.3464554 11.574401 1995-01-24 47078
## 145 1.3464554 6.742212 2002-04-24 47078
## 146 1.3464554 6.784653 1999-05-24 47078
## 147 1.3464554 13.791917 2014-09-24 47078
## 148 1.3464554 13.813879 1994-10-24 47078
## 149 1.3464554 7.114075 1985-02-25 47078
## 150 1.3464554 6.293584 1992-03-25 47078
## 151 1.3464554 9.300167 1995-07-25 47078
## 152 1.3464554 14.603178 1995-10-25 47078
## 153 1.3464554 13.767992 1997-11-25 47078
## 154 1.3464554 13.642127 1999-11-25 47078
## 155 1.3464554 10.097532 2000-01-26 47078
## 156 1.3464554 7.891046 1998-03-26 47078
## 157 1.3464554 10.047689 1994-07-26 47078
## 158 1.3464554 12.642313 1987-11-26 47078
## 159 1.3464554 12.875825 1993-10-27 47078
## 160 1.3464554 7.722097 1996-02-28 47078
## 161 1.3464554 7.107570 1998-04-28 47078
## 162 1.3464554 13.807156 1990-09-28 47078
## 163 1.3464554 13.902653 1995-09-28 47078
## 164 1.3464554 13.747459 2005-09-28 47078
## 165 1.3464554 13.733495 1991-10-28 47078
## 166 1.3464554 6.233358 2001-05-29 47078
## 167 1.3464554 7.573542 1995-06-29 47078
## 168 1.3464554 12.953400 1998-09-29 47078
## 169 1.3464554 13.309992 2000-09-29 47078
## 170 1.3464554 14.678620 1995-11-29 47078
## 171 1.3464554 5.212943 1987-04-30 47078
## 172 1.3464554 7.073730 1998-04-30 47078
## 173 1.3464554 14.110236 1999-09-30 47078
## 174 1.3464554 7.793126 1998-03-31 47078
## 175 1.3464554 6.969027 2000-05-31 47078
## 176 1.3464554 10.458418 2000-07-31 47078
## 177 1.4082478 13.889996 2001-11-01 47138
## 178 1.4082478 4.268993 2013-05-02 47138
## 179 1.4082478 5.277988 2009-04-03 47138
## 180 1.4082478 13.524884 2011-10-03 47138
## 181 1.4082478 12.492970 1991-12-03 47138
## 182 1.4082478 5.975603 1987-03-04 47138
## 183 1.4082478 6.517166 2017-04-04 47138
## 184 1.4082478 13.313321 2005-10-04 47138
## 185 1.4082478 4.717120 1986-06-05 47138
## 186 1.4082478 13.841129 2003-11-05 47138
## 187 1.4082478 13.597290 2004-11-05 47138
## 188 1.4082478 12.688597 1995-09-06 47138
## 189 1.4082478 9.599333 1993-01-07 47138
## 190 1.4082478 13.237070 2013-10-07 47138
## 191 1.4082478 7.185121 2007-05-08 47138
## 192 1.4082478 5.831162 2015-05-08 47138
## 193 1.4082478 6.485536 1987-07-08 47138
## 194 1.4082478 10.046354 1991-08-08 47138
## 195 1.4082478 13.583987 2014-10-08 47138
## 196 1.4082478 13.785021 2017-11-08 47138
## 197 1.4082478 10.131684 1989-01-10 47138
## 198 1.4082478 4.315384 1985-05-10 47138
## 199 1.4082478 11.057637 1985-09-10 47138
## 200 1.4082478 6.043803 2008-04-11 47138
## 201 1.4082478 4.950156 1987-05-11 47138
## 202 1.4082478 5.684071 1992-05-11 47138
## 203 1.4082478 6.157004 2004-05-11 47138
## 204 1.4082478 6.159373 1997-03-12 47138
## 205 1.4082478 6.293895 2005-04-12 47138
## 206 1.4082478 4.938523 1991-05-13 47138
## 207 1.4082478 12.138424 2000-09-13 47138
## 208 1.4082478 4.691975 2011-04-14 47138
## 209 1.4082478 12.903483 1996-10-14 47138
## 210 1.4082478 6.636885 2014-04-15 47138
## 211 1.4082478 11.726565 1990-08-15 47138
## 212 1.4082478 13.481020 2009-10-15 47138
## 213 1.4082478 12.295352 1988-11-15 47138
## 214 1.4082478 5.066844 2006-05-16 47138
## 215 1.4082478 12.526717 2015-10-16 47138
## 216 1.4082478 NA 2018-11-16 47138
## 217 1.4082478 6.182913 1989-04-17 47138
## 218 1.4082478 6.405208 2018-04-17 47138
## 219 1.4082478 5.968040 1988-05-17 47138
## 220 1.4082478 6.837101 1990-05-17 47138
## 221 1.4082478 11.319027 1987-09-17 47138
## 222 1.4082478 13.086066 1999-09-17 47138
## 223 1.4082478 6.351983 2002-04-18 47138
## 224 1.4082478 6.669453 2016-05-18 47138
## 225 1.4082478 5.440745 1994-05-19 47138
## 226 1.4082478 4.976360 1986-06-19 47138
## 227 1.4082478 9.773882 1986-08-19 47138
## 228 1.4082478 12.800709 2002-09-19 47138
## 229 1.4082478 12.082613 2012-09-19 47138
## 230 1.4082478 12.164218 1987-11-19 47138
## 231 1.4082478 7.199803 1998-03-20 47138
## 232 1.4082478 12.728235 2007-09-20 47138
## 233 1.4082478 5.394647 1993-04-22 47138
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## 1042 13.7468329 7.319719 2000-03-20 49881
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## 1093 0.7329067 NA 2018-09-11 50020
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## 1095 0.7329067 8.807794 2006-07-12 50020
## 1096 0.7329067 10.767163 2008-08-12 50020
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## 1173 12.4494716 6.430977 2008-04-09 50031
## 1174 12.4494716 13.431328 2001-10-09 50031
## 1175 12.4494716 NA 2018-10-09 50031
## 1176 12.4494716 6.535981 2015-04-10 50031
## 1177 12.4494716 12.756797 1988-10-10 50031
## 1178 12.4494716 13.823845 1997-10-10 50031
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## 1199 12.4494716 12.570414 2008-09-18 50031
## 1200 12.4494716 11.536128 1985-12-18 50031
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## 1209 12.4494716 13.286315 2005-09-21 50031
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## 1214 12.4494716 13.398921 2014-09-23 50031
## 1215 12.4494716 12.315054 2015-09-23 50031
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## 1223 12.4494716 6.323486 2004-04-28 50031
## 1224 12.4494716 13.109951 2010-09-28 50031
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## 1228 12.4494716 14.093418 2003-10-29 50031
## 1229 12.4494716 5.703683 1993-03-30 50031
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## 1231 12.4494716 13.322616 2007-10-30 50031
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## 1239 1.5656340 13.643310 2017-10-03 50139
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## 1255 1.5656340 14.407793 1995-10-09 50139
## 1256 1.5656340 5.779057 2011-05-10 50139
## 1257 1.5656340 NA 2018-09-11 50139
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## 1328 44.5857337 9.286463 2010-07-20 50257
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## 1379 3.6022840 7.434665 1990-03-20 50440
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## 1383 3.6022840 5.167997 2013-03-21 50440
## 1384 3.6022840 13.813543 2005-10-21 50440
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## 1392 3.6022840 6.435037 2017-04-24 50440
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## 1396 3.6022840 13.294808 2014-09-25 50440
## 1397 3.6022840 12.753473 1988-10-25 50440
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## 1399 3.6022840 13.191650 1991-10-26 50440
## 1400 3.6022840 7.824919 1988-06-27 50440
## 1401 3.6022840 13.015652 2007-09-27 50440
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## 1406 3.6022840 10.244192 1997-07-28 50440
## 1407 3.6022840 13.651434 1997-10-28 50440
## 1408 3.6022840 10.590756 1985-08-29 50440
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## 1602 3.6022840 4.921352 1994-05-09 51097
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## 1604 3.6022840 NA 2018-10-11 51097
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## 1680 3.2373385 6.277178 1993-05-10 51122
## 1681 3.2373385 NA 2018-07-10 51122
## 1682 3.2373385 NA 2018-10-10 51122
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## 1684 3.2373385 13.505904 2015-11-10 51122
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## 1729 1.9348647 11.674832 2010-09-09 51357
## 1730 1.9348647 7.755103 1992-02-10 51357
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## 1732 1.9348647 11.960411 1988-10-11 51357
## 1733 1.9348647 4.649469 2006-04-12 51357
## 1734 1.9348647 12.808848 2009-10-12 51357
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## 1737 1.9348647 11.909083 2002-09-13 51357
## 1738 1.9348647 12.460071 1991-10-13 51357
## 1739 1.9348647 4.641935 1993-04-14 51357
## 1740 1.9348647 12.629977 2008-10-14 51357
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## 1778 12.4494716 12.887047 1996-10-01 51392
## 1779 12.4494716 NA 2018-10-01 51392
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## 1782 12.4494716 10.844121 2013-09-03 51392
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## 1795 12.4494716 13.648595 2001-10-09 51392
## 1796 12.4494716 13.891486 2017-10-09 51392
## 1797 12.4494716 14.047175 1997-10-10 51392
## 1798 12.4494716 14.509773 1995-11-10 51392
## 1799 12.4494716 6.567336 2000-04-11 51392
## 1800 12.4494716 7.197180 2014-04-11 51392
## 1801 12.4494716 6.920886 2017-04-11 51392
## 1802 12.4494716 11.121210 2000-01-12 51392
## 1803 12.4494716 11.076494 1995-01-13 51392
## 1804 12.4494716 10.140023 2013-08-13 51392
## 1805 12.4494716 14.070534 2011-10-13 51392
## 1806 12.4494716 6.675515 2012-05-14 51392
## 1807 12.4494716 9.533868 1993-07-14 51392
## 1808 12.4494716 12.207966 2015-09-14 51392
## 1809 12.4494716 7.190339 2005-03-15 51392
## 1810 12.4494716 5.010035 1985-04-15 51392
## 1811 12.4494716 7.713133 1988-06-15 51392
## 1812 12.4494716 8.413756 1992-02-16 51392
## 1813 12.4494716 NA 2018-07-16 51392
## 1814 12.4494716 9.758419 1989-07-17 51392
## 1815 12.4494716 13.088556 1998-11-17 51392
## 1816 12.4494716 4.797406 1996-04-18 51392
## 1817 12.4494716 5.211888 2011-04-18 51392
## 1818 12.4494716 7.309181 1990-05-18 51392
## 1819 12.4494716 12.785065 2008-09-18 51392
## 1820 12.4494716 11.753631 1985-12-18 51392
## 1821 12.4494716 6.834448 2002-04-19 51392
## 1822 12.4494716 4.796349 2013-04-19 51392
## 1823 12.4494716 10.407814 1990-07-19 51392
## 1824 12.4494716 7.536238 1991-02-20 51392
## 1825 12.4494716 6.552497 2015-04-20 51392
## 1826 12.4494716 13.120535 1987-10-20 51392
## 1827 12.4494716 15.204039 2006-10-20 51392
## 1828 12.4494716 6.309051 2006-03-21 51392
## 1829 12.4494716 13.503794 2005-09-21 51392
## 1830 12.4494716 3.866423 1986-04-22 51392
## 1831 12.4494716 6.810244 1995-05-22 51392
## 1832 12.4494716 13.659634 2007-10-22 51392
## 1833 12.4494716 13.614309 2014-09-23 51392
## 1834 12.4494716 5.585251 1987-03-24 51392
## 1835 12.4494716 7.779697 1988-02-25 51392
## 1836 12.4494716 7.994371 1999-02-26 51392
## 1837 12.4494716 7.507525 1998-03-26 51392
## 1838 12.4494716 5.880753 2009-03-26 51392
## 1839 12.4494716 6.455496 1997-05-27 51392
## 1840 12.4494716 9.206220 2017-06-27 51392
## 1841 12.4494716 13.468801 1982-09-27 51392
## 1842 12.4494716 6.513485 2004-04-28 51392
## 1843 12.4494716 13.334474 2010-09-28 51392
## 1844 12.4494716 9.472199 1991-07-29 51392
## 1845 12.4494716 13.687069 1992-09-29 51392
## 1846 12.4494716 14.318852 2003-10-29 51392
## 1847 12.4494716 5.885718 1993-03-30 51392
## 1848 12.4494716 5.532015 1994-03-30 51392
## 1849 12.4494716 13.512248 1989-11-30 51392
## 1850 12.4494716 13.611662 1991-10-31 51392
## 1851 0.7113656 4.719331 2013-05-01 51634
## 1852 0.7113656 14.606545 2003-10-01 51634
## 1853 0.7113656 5.354198 2001-05-03 51634
## 1854 0.7113656 11.337087 1986-09-04 51634
## 1855 0.7113656 8.466111 1993-02-05 51634
## 1856 0.7113656 11.583933 1992-08-05 51634
## 1857 0.7113656 14.675530 1995-11-05 51634
## 1858 0.7113656 9.758327 1987-08-06 51634
## 1859 0.7113656 7.764536 1989-03-07 51634
## 1860 0.7113656 9.240808 1993-07-07 51634
## 1861 0.7113656 14.097985 1992-10-07 51634
## 1862 0.7113656 13.789706 2007-10-08 51634
## 1863 0.7113656 5.949994 1991-04-09 51634
## 1864 0.7113656 7.949558 1991-07-09 51634
## 1865 0.7113656 12.455215 2000-09-09 51634
## 1866 0.7113656 13.186309 1999-12-10 51634
## 1867 0.7113656 6.325708 1985-03-11 51634
## 1868 0.7113656 6.831718 1994-06-11 51634
## 1869 0.7113656 11.631038 1985-09-11 51634
## 1870 0.7113656 12.304925 2015-09-11 51634
## 1871 0.7113656 14.080821 2005-10-11 51634
## 1872 0.7113656 6.946717 1992-03-13 51634
## 1873 0.7113656 6.669733 1997-03-13 51634
## 1874 0.7113656 7.309751 1998-05-13 51634
## 1875 0.7113656 6.783005 2002-05-13 51634
## 1876 0.7113656 13.761679 2008-10-13 51634
## 1877 0.7113656 6.224436 2003-04-15 51634
## 1878 0.7113656 13.654243 1991-10-15 51634
## 1879 0.7113656 12.412028 2013-09-16 51634
## 1880 0.7113656 6.842800 1995-04-17 51634
## 1881 0.7113656 7.490070 2007-04-17 51634
## 1882 0.7113656 12.849866 1998-09-17 51634
## 1883 0.7113656 6.763412 2000-05-18 51634
## 1884 0.7113656 15.274356 2006-10-18 51634
## 1885 0.7113656 7.222368 1987-02-19 51634
## 1886 0.7113656 5.236578 1994-04-19 51634
## 1887 0.7113656 13.788808 1997-11-19 51634
## 1888 0.7113656 13.475104 1989-09-20 51634
## 1889 0.7113656 13.718615 1994-10-20 51634
## 1890 0.7113656 6.669659 2005-04-21 51634
## 1891 0.7113656 6.456259 1988-03-22 51634
## 1892 0.7113656 5.634244 2009-04-22 51634
## 1893 0.7113656 12.685286 1988-09-22 51634
## 1894 0.7113656 13.706840 2004-09-22 51634
## 1895 0.7113656 13.420162 1996-11-22 51634
## 1896 0.7113656 6.382373 2004-04-23 51634
## 1897 0.7113656 6.992593 1986-02-24 51634
## 1898 0.7113656 6.302063 2008-04-25 51634
## 1899 0.7113656 13.781544 1990-11-26 51634
## 1900 0.7113656 7.634378 1990-03-27 51634
## 1901 0.7113656 5.496103 2006-04-27 51634
## 1902 0.7113656 6.432028 2015-04-27 51634
## 1903 0.7113656 13.311575 2002-11-28 51634
## 1904 0.7113656 13.030492 1990-08-30 51634
## 1905 0.7113656 13.894031 2009-09-30 51634
## 1906 1.4082478 11.462162 1988-12-01 52265
## 1907 1.4082478 7.962350 1997-07-02 52265
## 1908 1.4082478 12.971064 2002-10-02 52265
## 1909 1.4082478 12.714866 2013-10-02 52265
## 1910 1.4082478 4.542099 1986-06-03 52265
## 1911 1.4082478 12.648828 1994-10-03 52265
## 1912 1.4082478 10.275179 1988-01-04 52265
## 1913 1.4082478 7.367163 1987-02-04 52265
## 1914 1.4082478 4.325400 2010-05-04 52265
## 1915 1.4082478 5.780916 1985-03-05 52265
## 1916 1.4082478 13.023556 2010-10-05 52265
## 1917 1.4082478 7.538796 1990-03-07 52265
## 1918 1.4082478 4.272536 2013-05-07 52265
## 1919 1.4082478 6.982938 1995-03-08 52265
## 1920 1.4082478 6.015712 2015-04-09 52265
## 1921 1.4082478 5.747527 1991-03-11 52265
## 1922 1.4082478 5.688593 1991-06-11 52265
## 1923 1.4082478 11.591704 1996-12-11 52265
## 1924 1.4082478 13.817363 1995-10-12 52265
## 1925 1.4082478 12.675667 1998-11-12 52265
## 1926 1.4082478 12.338060 2015-10-13 52265
## 1927 1.4082478 7.886641 1990-06-14 52265
## 1928 1.4082478 7.463932 2016-03-15 52265
## 1929 1.4082478 7.066360 1993-02-17 52265
## 1930 1.4082478 7.096444 1998-03-17 52265
## 1931 1.4082478 9.569815 1989-01-18 52265
## 1932 1.4082478 7.110895 2007-05-18 52265
## 1933 1.4082478 12.326665 1991-09-18 52265
## 1934 1.4082478 7.534579 1992-02-19 52265
## 1935 1.4082478 13.426849 2004-10-19 52265
## 1936 1.4082478 12.024354 1985-11-19 52265
## 1937 1.4082478 9.331024 1989-07-20 52265
## 1938 1.4082478 9.509325 1992-07-20 52265
## 1939 1.4082478 7.228001 1993-06-21 52265
## 1940 1.4082478 12.723017 1992-09-21 52265
## 1941 1.4082478 13.522812 1997-10-21 52265
## 1942 1.4082478 6.012001 1994-02-22 52265
## 1943 1.4082478 11.975160 1993-09-23 52265
## 1944 1.4082478 6.296137 2000-05-24 52265
## 1945 1.4082478 NA 2018-09-24 52265
## 1946 1.4082478 13.471915 2016-10-24 52265
## 1947 1.4082478 12.902353 1990-09-25 52265
## 1948 1.4082478 12.919408 2007-10-25 52265
## 1949 1.4082478 4.119332 1996-04-26 52265
## 1950 1.4082478 12.865972 2013-11-26 52265
## 1951 1.4082478 13.551705 1999-10-27 52265
## 1952 1.4082478 5.827098 2004-03-29 52265
## 1953 1.4082478 7.289345 1994-06-29 52265
## 1954 1.4082478 8.341080 1985-07-29 52265
## 1955 1.4082478 4.167979 1985-04-30 52265
## 1956 1.4082478 3.994043 2018-05-30 52265
## 1957 1.4082478 7.616885 1988-06-30 52265
## 1958 1.4082478 12.250224 2000-11-30 52265
## 1959 1.4082478 12.946676 2001-11-30 52265
## 1960 0.7113656 13.851439 2004-10-01 52480
## 1961 0.7113656 6.323458 2004-04-02 52480
## 1962 0.7113656 6.654342 1995-04-03 52480
## 1963 0.7113656 5.170042 2001-05-03 52480
## 1964 0.7113656 13.720063 1989-10-03 52480
## 1965 0.7113656 12.486328 1993-11-03 52480
## 1966 0.7113656 5.137776 2006-05-04 52480
## 1967 0.7113656 13.360297 2001-10-04 52480
## 1968 0.7113656 7.458308 2007-04-05 52480
## 1969 0.7113656 5.950864 1993-05-05 52480
## 1970 0.7113656 6.093473 2015-05-05 52480
## 1971 0.7113656 11.395888 1992-08-05 52480
## 1972 0.7113656 4.884163 2010-05-06 52480
## 1973 0.7113656 13.025823 1985-11-06 52480
## 1974 0.7113656 6.202818 2008-05-07 52480
## 1975 0.7113656 6.865148 2014-05-07 52480
## 1976 0.7113656 13.627274 2010-10-07 52480
## 1977 0.7113656 11.579052 1990-08-08 52480
## 1978 0.7113656 5.443751 1994-05-09 52480
## 1979 0.7113656 7.344023 1996-07-10 52480
## 1980 0.7113656 10.709961 1993-08-10 52480
## 1981 0.7113656 12.524269 1987-11-10 52480
## 1982 0.7113656 6.110710 1988-05-12 52480
## 1983 0.7113656 5.330183 1986-06-12 52480
## 1984 0.7113656 11.644295 1997-08-12 52480
## 1985 0.7113656 12.557947 1986-11-12 52480
## 1986 0.7113656 13.329014 1999-09-13 52480
## 1987 0.7113656 13.931152 2005-10-13 52480
## 1988 0.7113656 13.823768 2009-10-13 52480
## 1989 0.7113656 14.416557 1995-11-14 52480
## 1990 0.7113656 7.585805 2002-03-15 52480
## 1991 0.7113656 7.013829 2005-03-16 52480
## 1992 0.7113656 6.087623 2003-04-16 52480
## 1993 0.7113656 13.909139 1990-11-16 52480
## 1994 0.7113656 13.126906 1992-11-16 52480
## 1995 0.7113656 12.645071 2008-09-17 52480
## 1996 0.7113656 6.596520 2018-04-18 52480
## 1997 0.7113656 6.594682 2000-05-18 52480
## 1998 0.7113656 12.333864 2015-09-18 52480
## 1999 0.7113656 13.639866 2007-10-18 52480
## 2000 0.7113656 11.675312 1996-12-19 52480
## 2001 0.7113656 8.299655 1989-06-20 52480
## 2002 0.7113656 5.296898 1987-05-21 52480
## 2003 0.7113656 6.540752 1992-05-21 52480
## 2004 0.7113656 7.310794 1998-05-21 52480
## 2005 0.7113656 13.160425 1991-11-21 52480
## 2006 0.7113656 14.619834 2006-11-21 52480
## 2007 0.7113656 12.471808 1994-12-21 52480
## 2008 0.7113656 5.444773 2009-04-22 52480
## 2009 0.7113656 4.887276 1985-05-23 52480
## 2010 0.7113656 5.520759 1991-05-23 52480
## 2011 0.7113656 13.045823 1988-10-24 52480
## 2012 0.7113656 12.493738 1998-11-25 52480
## 2013 0.7113656 13.927936 2003-11-25 52480
## 2014 0.7113656 9.882948 1994-07-27 52480
## 2015 0.7113656 13.466114 1997-11-27 52480
## 2016 0.7113656 12.771946 2000-11-28 52480
## 2017 0.7113656 NA 2018-10-30 52480
## 2018 0.7113656 13.039042 2002-11-30 52480
## 2019 12.4494716 6.949518 1990-05-01 52491
## 2020 12.4494716 6.584499 2003-04-03 52491
## 2021 12.4494716 12.317808 2008-09-03 52491
## 2022 12.4494716 13.972986 1989-10-03 52491
## 2023 12.4494716 6.456655 1987-03-05 52491
## 2024 12.4494716 6.917529 1997-03-05 52491
## 2025 12.4494716 6.610957 2013-03-05 52491
## 2026 12.4494716 9.729928 1990-07-05 52491
## 2027 12.4494716 14.450287 1995-10-05 52491
## 2028 12.4494716 13.783437 2007-10-05 52491
## 2029 12.4494716 13.948835 2009-10-05 52491
## 2030 12.4494716 8.637209 1988-07-06 52491
## 2031 12.4494716 13.618776 2000-10-06 52491
## 2032 12.4494716 13.371334 1998-10-07 52491
## 2033 12.4494716 14.612244 2003-10-07 52491
## 2034 12.4494716 13.764256 1991-11-07 52491
## 2035 12.4494716 8.405564 1993-02-08 52491
## 2036 12.4494716 6.573567 2000-05-09 52491
## 2037 12.4494716 6.887270 1994-06-09 52491
## 2038 12.4494716 7.050781 1995-04-10 52491
## 2039 12.4494716 7.518450 1993-06-10 52491
## 2040 12.4494716 12.088048 1987-09-10 52491
## 2041 12.4494716 13.373034 1997-09-10 52491
## 2042 12.4494716 7.285973 2012-04-11 52491
## 2043 12.4494716 13.939287 2011-11-11 52491
## 2044 12.4494716 11.824871 1988-12-12 52491
## 2045 12.4494716 6.968446 1994-06-13 52491
## 2046 12.4494716 13.515506 2005-09-14 52491
## 2047 12.4494716 8.599493 1988-02-15 52491
## 2048 12.4494716 6.171734 1987-06-15 52491
## 2049 12.4494716 14.387648 1990-10-15 52491
## 2050 12.4494716 12.932212 2012-11-15 52491
## 2051 12.4494716 6.873830 2008-05-16 52491
## 2052 12.4494716 7.238408 1994-02-17 52491
## 2053 12.4494716 6.725306 1989-04-17 52491
## 2054 12.4494716 13.251141 2010-09-17 52491
## 2055 12.4494716 6.701301 1992-03-18 52491
## 2056 12.4494716 6.789077 1991-06-18 52491
## 2057 12.4494716 13.268727 2002-09-18 52491
## 2058 12.4494716 7.602201 2007-04-19 52491
## 2059 12.4494716 13.856838 2013-11-19 52491
## 2060 12.4494716 13.043786 1994-09-21 52491
## 2061 12.4494716 13.727497 2004-09-23 52491
## 2062 12.4494716 6.876589 1999-03-24 52491
## 2063 12.4494716 6.700759 2004-03-24 52491
## 2064 12.4494716 5.780130 2010-03-24 52491
## 2065 12.4494716 4.870350 1996-04-24 52491
## 2066 12.4494716 7.114023 2014-04-24 52491
## 2067 12.4494716 13.480516 1996-10-24 52491
## 2068 12.4494716 7.011578 2005-05-25 52491
## 2069 12.4494716 13.284859 2001-09-26 52491
## 2070 12.4494716 5.370590 2011-03-28 52491
## 2071 12.4494716 7.021564 1998-04-28 52491
## 2072 12.4494716 13.826932 1992-09-29 52491
## 2073 12.4494716 14.047609 2014-09-29 52491
## 2074 12.4494716 9.759850 1991-01-30 52491
## 2075 12.4494716 9.117949 1992-06-30 52491
## 2076 12.4494716 12.956813 1993-09-30 52491
## 2077 16.9800748 11.235472 1990-08-01 52718
## 2078 16.9800748 4.640442 1996-05-02 52718
## 2079 16.9800748 11.212076 1985-09-03 52718
## 2080 16.9800748 13.483684 1994-11-04 52718
## 2081 16.9800748 14.140160 1990-11-05 52718
## 2082 16.9800748 8.457613 1994-07-06 52718
## 2083 16.9800748 11.426175 1990-08-06 52718
## 2084 16.9800748 7.326729 1987-07-08 52718
## 2085 16.9800748 7.790252 1991-07-08 52718
## 2086 16.9800748 7.126541 1990-05-10 52718
## 2087 16.9800748 5.136673 1994-04-12 52718
## 2088 16.9800748 6.609038 2005-05-12 52718
## 2089 16.9800748 12.608352 1987-11-12 52718
## 2090 16.9800748 7.495103 1988-06-13 52718
## 2091 16.9800748 11.920592 1992-08-13 52718
## 2092 16.9800748 7.752908 1998-03-16 52718
## 2093 16.9800748 7.255890 2014-05-16 52718
## 2094 16.9800748 NA 2018-11-16 52718
## 2095 16.9800748 12.969507 1993-10-17 52718
## 2096 16.9800748 14.143591 2017-10-17 52718
## 2097 16.9800748 6.182541 2008-04-18 52718
## 2098 16.9800748 8.371355 1992-06-18 52718
## 2099 16.9800748 14.088208 2016-10-18 52718
## 2100 16.9800748 13.222697 2015-11-18 52718
## 2101 16.9800748 7.347351 2016-04-19 52718
## 2102 16.9800748 13.837427 1995-09-20 52718
## 2103 16.9800748 14.170412 1997-10-20 52718
## 2104 16.9800748 7.866363 1993-06-21 52718
## 2105 16.9800748 13.595645 1991-10-21 52718
## 2106 16.9800748 12.523325 1988-11-21 52718
## 2107 16.9800748 5.816790 1993-04-22 52718
## 2108 16.9800748 6.436592 2015-05-22 52718
## 2109 16.9800748 6.967195 1986-07-22 52718
## 2110 16.9800748 6.684551 1995-04-23 52718
## 2111 16.9800748 8.465019 1985-07-23 52718
## 2112 16.9800748 13.000309 1998-09-23 52718
## 2113 16.9800748 13.997079 2005-11-23 52718
## 2114 16.9800748 5.329676 1991-04-24 52718
## 2115 16.9800748 13.386820 1996-10-24 52718
## 2116 16.9800748 6.763962 2017-04-25 52718
## 2117 16.9800748 13.658028 1989-09-25 52718
## 2118 16.9800748 5.956991 1986-06-26 52718
## 2119 16.9800748 12.808556 1992-11-26 52718
## 2120 16.9800748 8.987178 1993-07-27 52718
## 2121 16.9800748 5.987957 1992-04-29 52718
## 2122 16.9800748 5.714292 1997-04-29 52718
## 2123 16.9800748 13.414142 1999-11-29 52718
## 2124 16.9800748 6.885168 1989-03-30 52718
## 2125 16.9800748 4.644046 2018-05-30 52718
## 2126 16.9800748 13.702392 2008-10-30 52718
## 2127 0.7113656 14.610161 2003-10-01 53594
## 2128 0.7113656 14.437550 2016-11-01 53594
## 2129 0.7113656 7.341967 2014-04-02 53594
## 2130 0.7113656 4.788011 2013-05-02 53594
## 2131 0.7113656 5.378066 2001-05-03 53594
## 2132 0.7113656 11.340760 1986-09-04 53594
## 2133 0.7113656 8.486155 1993-02-05 53594
## 2134 0.7113656 11.594728 1992-08-05 53594
## 2135 0.7113656 9.773323 1987-08-06 53594
## 2136 0.7113656 7.831358 1989-03-07 53594
## 2137 0.7113656 9.263588 1993-07-07 53594
## 2138 0.7113656 14.081383 1992-10-07 53594
## 2139 0.7113656 14.402904 2017-11-07 53594
## 2140 0.7113656 NA 2018-11-07 53594
## 2141 0.7113656 13.073934 2011-09-08 53594
## 2142 0.7113656 13.788458 2007-10-08 53594
## 2143 0.7113656 14.526204 1995-11-08 53594
## 2144 0.7113656 5.997480 1991-04-09 53594
## 2145 0.7113656 7.995087 1991-07-09 53594
## 2146 0.7113656 12.455462 2000-09-09 53594
## 2147 0.7113656 13.201145 1999-12-10 53594
## 2148 0.7113656 6.397200 1985-03-11 53594
## 2149 0.7113656 6.849151 1994-06-11 53594
## 2150 0.7113656 11.631814 1985-09-11 53594
## 2151 0.7113656 12.298194 2015-09-11 53594
## 2152 0.7113656 14.082718 2005-10-11 53594
## 2153 0.7113656 5.339967 2010-04-12 53594
## 2154 0.7113656 7.010052 1992-03-13 53594
## 2155 0.7113656 6.734011 1997-03-13 53594
## 2156 0.7113656 7.358772 1998-05-13 53594
## 2157 0.7113656 6.822613 2002-05-13 53594
## 2158 0.7113656 13.768670 2008-10-13 53594
## 2159 0.7113656 14.293594 2014-11-13 53594
## 2160 0.7113656 6.270488 2003-04-15 53594
## 2161 0.7113656 6.074706 2009-05-15 53594
## 2162 0.7113656 6.586049 2012-05-15 53594
## 2163 0.7113656 7.733884 1986-07-15 53594
## 2164 0.7113656 13.666291 1991-10-15 53594
## 2165 0.7113656 13.997404 2013-10-16 53594
## 2166 0.7113656 6.874332 1995-04-17 53594
## 2167 0.7113656 7.524546 2007-04-17 53594
## 2168 0.7113656 12.847574 1998-09-17 53594
## 2169 0.7113656 6.807345 2000-05-18 53594
## 2170 0.7113656 15.261096 2006-10-18 53594
## 2171 0.7113656 7.275668 1987-02-19 53594
## 2172 0.7113656 5.267277 1994-04-19 53594
## 2173 0.7113656 13.785132 1997-11-19 53594
## 2174 0.7113656 5.101933 1985-05-20 53594
## 2175 0.7113656 13.453351 1989-09-20 53594
## 2176 0.7113656 12.646355 2012-09-20 53594
## 2177 0.7113656 13.702853 1994-10-20 53594
## 2178 0.7113656 6.740613 2005-04-21 53594
## 2179 0.7113656 6.501931 1988-03-22 53594
## 2180 0.7113656 4.861475 2018-05-22 53594
## 2181 0.7113656 12.704140 1988-09-22 53594
## 2182 0.7113656 13.713684 2004-09-22 53594
## 2183 0.7113656 13.431700 1996-11-22 53594
## 2184 0.7113656 7.880989 2016-03-23 53594
## 2185 0.7113656 6.434253 2004-04-23 53594
## 2186 0.7113656 7.037436 1986-02-24 53594
## 2187 0.7113656 6.345482 2008-04-25 53594
## 2188 0.7113656 13.900964 2010-10-25 53594
## 2189 0.7113656 13.776105 1990-11-26 53594
## 2190 0.7113656 7.670970 1990-03-27 53594
## 2191 0.7113656 5.557854 2006-04-27 53594
## 2192 0.7113656 5.593426 2011-04-27 53594
## 2193 0.7113656 6.472019 2015-04-27 53594
## 2194 0.7113656 6.750267 1996-06-27 53594
## 2195 0.7113656 12.373037 1985-11-28 53594
## 2196 0.7113656 7.869569 2017-05-30 53594
## 2197 0.7113656 13.031663 1990-08-30 53594
## 2198 0.7113656 13.892261 2009-09-30 53594
## 2199 0.7113656 13.688890 2001-11-30 53594
## 2200 1.4082478 13.303372 2002-10-02 53846
## 2201 1.4082478 7.030589 2002-04-03 53846
## 2202 1.4082478 4.866451 1986-06-03 53846
## 2203 1.4082478 10.845466 1986-09-03 53846
## 2204 1.4082478 13.006592 1994-10-03 53846
## 2205 1.4082478 8.895716 1985-02-04 53846
## 2206 1.4082478 6.103482 1987-03-04 53846
## 2207 1.4082478 6.646750 2017-04-04 53846
## 2208 1.4082478 7.963423 1985-03-05 53846
## 2209 1.4082478 NA 2018-11-05 53846
## 2210 1.4082478 7.915980 1990-03-06 53846
## 2211 1.4082478 13.370913 2013-10-07 53846
## 2212 1.4082478 6.223732 1999-04-08 53846
## 2213 1.4082478 7.032431 1987-07-08 53846
## 2214 1.4082478 14.264491 2003-10-08 53846
## 2215 1.4082478 5.911839 2003-04-09 53846
## 2216 1.4082478 13.745302 2011-10-10 53846
## 2217 1.4082478 13.065446 1998-11-10 53846
## 2218 1.4082478 6.076239 1991-03-11 53846
## 2219 1.4082478 6.017035 1991-06-11 53846
## 2220 1.4082478 14.172068 1995-10-12 53846
## 2221 1.4082478 4.815888 2011-04-13 53846
## 2222 1.4082478 7.195801 1988-06-13 53846
## 2223 1.4082478 12.681465 2015-10-13 53846
## 2224 1.4082478 8.227195 1990-06-14 53846
## 2225 1.4082478 6.769123 2014-04-15 53846
## 2226 1.4082478 13.717672 1997-10-15 53846
## 2227 1.4082478 6.322976 2015-04-16 53846
## 2228 1.4082478 7.403773 1993-02-17 53846
## 2229 1.4082478 7.427283 1998-03-17 53846
## 2230 1.4082478 4.476249 1996-04-17 53846
## 2231 1.4082478 12.631524 1991-09-17 53846
## 2232 1.4082478 14.855610 2006-10-17 53846
## 2233 1.4082478 13.839545 2017-10-17 53846
## 2234 1.4082478 9.895117 1989-01-18 53846
## 2235 1.4082478 7.864124 1992-02-19 53846
## 2236 1.4082478 12.219449 2012-09-19 53846
## 2237 1.4082478 13.907502 2014-10-19 53846
## 2238 1.4082478 12.365051 1985-11-19 53846
## 2239 1.4082478 9.675341 1989-07-20 53846
## 2240 1.4082478 9.846825 1992-07-20 53846
## 2241 1.4082478 4.749076 2013-05-21 53846
## 2242 1.4082478 7.567679 1993-06-21 53846
## 2243 1.4082478 13.069419 1992-09-21 53846
## 2244 1.4082478 6.351877 1994-02-22 53846
## 2245 1.4082478 6.339607 2012-05-22 53846
## 2246 1.4082478 8.093399 1985-07-22 53846
## 2247 1.4082478 13.632448 2009-10-22 53846
## 2248 1.4082478 12.989311 1996-11-22 53846
## 2249 1.4082478 5.831934 2006-03-23 53846
## 2250 1.4082478 5.633583 2009-03-23 53846
## 2251 1.4082478 12.324187 1993-09-23 53846
## 2252 1.4082478 7.523922 2016-03-24 53846
## 2253 1.4082478 6.633823 2000-05-24 53846
## 2254 1.4082478 6.464267 1986-02-25 53846
## 2255 1.4082478 13.248030 1990-09-25 53846
## 2256 1.4082478 5.267301 1986-06-26 53846
## 2257 1.4082478 13.901716 2016-10-27 53846
## 2258 1.4082478 13.369852 1989-11-27 53846
## 2259 1.4082478 13.888862 1999-10-28 53846
## 2260 1.4082478 6.561862 1995-03-29 53846
## 2261 1.4082478 7.632527 1994-06-29 53846
## 2262 1.4082478 9.030766 1985-01-30 53846
## 2263 1.4082478 5.900985 1988-03-30 53846
## 2264 1.4082478 4.483808 1985-04-30 53846
## 2265 1.4082478 4.340594 2018-05-30 53846
## 2266 1.4082478 7.577229 1988-06-30 53846
## 2267 1.4082478 8.100760 1997-06-30 53846
## 2268 1.4082478 12.600461 2000-11-30 53846
## 2269 12.4494716 6.782362 1990-05-02 53961
## 2270 12.4494716 9.014345 1992-07-02 53961
## 2271 12.4494716 6.366815 2003-04-03 53961
## 2272 12.4494716 12.852487 1991-12-03 53961
## 2273 12.4494716 8.418641 1993-02-04 53961
## 2274 12.4494716 13.917831 2009-11-04 53961
## 2275 12.4494716 5.180184 2006-05-05 53961
## 2276 12.4494716 13.911472 1992-10-05 53961
## 2277 12.4494716 14.268807 1995-10-05 53961
## 2278 12.4494716 13.442700 2000-10-06 53961
## 2279 12.4494716 13.198621 1998-10-07 53961
## 2280 12.4494716 7.158447 1993-06-08 53961
## 2281 12.4494716 6.354238 2000-05-09 53961
## 2282 12.4494716 9.748179 1990-07-09 53961
## 2283 12.4494716 14.046267 1989-10-09 53961
## 2284 12.4494716 6.830575 1995-04-10 53961
## 2285 12.4494716 13.204309 1997-09-10 53961
## 2286 12.4494716 7.227900 2005-03-11 53961
## 2287 12.4494716 8.733054 1988-07-12 53961
## 2288 12.4494716 13.728514 2010-10-12 53961
## 2289 12.4494716 11.648346 1988-12-12 53961
## 2290 12.4494716 9.454556 1989-07-13 53961
## 2291 12.4494716 7.275848 1994-02-14 53961
## 2292 12.4494716 6.910135 1994-06-14 53961
## 2293 12.4494716 8.411121 1988-02-15 53961
## 2294 12.4494716 6.802134 2002-05-15 53961
## 2295 12.4494716 6.518106 2012-05-15 53961
## 2296 12.4494716 14.225570 1990-10-15 53961
## 2297 12.4494716 6.511985 1989-04-17 53961
## 2298 12.4494716 6.488810 1992-03-18 53961
## 2299 12.4494716 6.586327 1991-06-18 53961
## 2300 12.4494716 13.114750 2002-09-18 53961
## 2301 12.4494716 12.802490 1994-09-19 53961
## 2302 12.4494716 8.265212 2007-03-20 53961
## 2303 12.4494716 5.734452 1997-04-21 53961
## 2304 12.4494716 6.660290 1998-04-21 53961
## 2305 12.4494716 13.465000 2005-09-21 53961
## 2306 12.4494716 13.795101 2008-10-22 53961
## 2307 12.4494716 6.907066 2014-04-23 53961
## 2308 12.4494716 6.856315 2008-05-23 53961
## 2309 12.4494716 12.601373 1993-09-23 53961
## 2310 12.4494716 6.643067 1999-03-24 53961
## 2311 12.4494716 4.648360 1996-04-24 53961
## 2312 12.4494716 13.315213 1996-10-24 53961
## 2313 12.4494716 13.112675 2001-09-26 53961
## 2314 12.4494716 13.389947 2007-09-26 53961
## 2315 12.4494716 9.775043 1991-01-28 53961
## 2316 12.4494716 5.521827 2009-04-29 53961
## 2317 12.4494716 5.023943 2010-04-29 53961
## 2318 12.4494716 13.908143 2014-09-30 53961
## 2319 12.4494716 12.964718 2012-10-30 53961#Anglian
##By Site -ACHE
SITE_IDs = unique(anglaindataMOA$SITE_ID)
anglaindataMOA_pest_rich_plots = list()
for(SITE_ID_ in SITE_IDs) {
anglaindataMOA_pest_rich_plots[[SITE_ID_]] = ggplot(anglaindataMOA %>% filter(SITE_ID == SITE_ID_), aes(x=AChE, y=distinctfamilies)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + geom_smooth(method = "lm", se = FALSE) + theme_bw() + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10')
print(anglaindataMOA_pest_rich_plots[[SITE_ID_]])
#ggsave(anglaindataMOA_pest_rich_plots[[SITE_ID_]], file=paste0("plot_", SITE_ID_," AChE Angalian.png"), dpi=300)
}## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 54 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 54 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 52 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 52 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 94 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 94 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 54 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 54 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 54 rows containing non-finite values (`stat_smooth()`).
## Removed 54 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 55 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 55 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 63 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 63 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 58 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 58 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 67 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 67 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 58 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 58 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 50 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 50 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 46 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 46 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 83 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 83 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 53 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 53 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 41 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 41 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 107 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 107 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 64 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 64 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 65 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 65 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 52 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 52 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 59 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 59 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 67 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 67 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 49 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 49 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 63 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 63 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 65 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 65 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 65 rows containing non-finite values (`stat_smooth()`).
## Removed 65 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 59 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 59 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 56 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 56 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 51 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 51 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 64 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 64 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 63 rows containing non-finite values (`stat_smooth()`).## Warning: Removed 63 rows containing missing values (`geom_point()`).
##By Site -GABA
SITE_IDs = unique(anglaindataMOA$SITE_ID)
anglaindataMOA_pest_rich_plots = list()
for(SITE_ID_ in SITE_IDs) {
anglaindataMOA_pest_rich_plots[[SITE_ID_]] = ggplot(anglaindataMOA %>% filter(SITE_ID == SITE_ID_), aes(x=GABA_receptor, y=distinctfamilies)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme_bw() + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10')
print(anglaindataMOA_pest_rich_plots[[SITE_ID_]])
#ggsave(anglaindataMOA_pest_rich_plots[[SITE_ID_]], file=paste0("plot_", SITE_ID_," GABA Angalian.png"), dpi=300)
}## Warning: Removed 58 rows containing missing values (`geom_point()`).
## Warning: Removed 56 rows containing missing values (`geom_point()`).
## Warning: Removed 94 rows containing missing values (`geom_point()`).
## Warning: Removed 54 rows containing missing values (`geom_point()`).
## Warning: Removed 54 rows containing missing values (`geom_point()`).
## Warning: Removed 55 rows containing missing values (`geom_point()`).
## Warning: Removed 63 rows containing missing values (`geom_point()`).
## Warning: Removed 32 rows containing missing values (`geom_point()`).
## Warning: Removed 67 rows containing missing values (`geom_point()`).
## Warning: Removed 58 rows containing missing values (`geom_point()`).
## Warning: Removed 41 rows containing missing values (`geom_point()`).
## Warning: Removed 30 rows containing missing values (`geom_point()`).
## Warning: Removed 83 rows containing missing values (`geom_point()`).
## Warning: Removed 53 rows containing missing values (`geom_point()`).
## Warning: Removed 41 rows containing missing values (`geom_point()`).
## Warning: Removed 107 rows containing missing values (`geom_point()`).
## Warning: Removed 64 rows containing missing values (`geom_point()`).
## Warning: Removed 65 rows containing missing values (`geom_point()`).
## Warning: Removed 52 rows containing missing values (`geom_point()`).
## Warning: Removed 59 rows containing missing values (`geom_point()`).
## Warning: Removed 67 rows containing missing values (`geom_point()`).
## Warning: Removed 30 rows containing missing values (`geom_point()`).
## Warning: Removed 63 rows containing missing values (`geom_point()`).
## Warning: Removed 65 rows containing missing values (`geom_point()`).
## Warning: Removed 65 rows containing missing values (`geom_point()`).
## Warning: Removed 59 rows containing missing values (`geom_point()`).
## Warning: Removed 56 rows containing missing values (`geom_point()`).
## Warning: Removed 51 rows containing missing values (`geom_point()`).
## Warning: Removed 38 rows containing missing values (`geom_point()`).
## Warning: Removed 63 rows containing missing values (`geom_point()`).
#Midland
##By Site - ACHE
SITE_IDs = unique(midlandsdataMOA$SITE_ID)
midlandsdataMOA_pest_rich_plots = list()
for(SITE_ID_ in SITE_IDs) {
midlandsdataMOA_pest_rich_plots[[SITE_ID_]] = ggplot(midlandsdataMOA %>% filter(SITE_ID == SITE_ID_), aes(x=AChE, y=distinct_families)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme_bw() + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10')
print(midlandsdataMOA_pest_rich_plots[[SITE_ID_]])
ggsave(midlandsdataMOA_pest_rich_plots[[SITE_ID_]], file=paste0("plot_", SITE_ID_," AChE Midland.png"), dpi=300)
}## Warning: Removed 68 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 68 rows containing missing values (`geom_point()`).
## Warning: Removed 107 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 107 rows containing missing values (`geom_point()`).
## Warning: Removed 83 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 83 rows containing missing values (`geom_point()`).
## Warning: Removed 36 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 36 rows containing missing values (`geom_point()`).
## Warning: Removed 45 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 45 rows containing missing values (`geom_point()`).
## Warning: Removed 70 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 70 rows containing missing values (`geom_point()`).
## Warning: Removed 52 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 52 rows containing missing values (`geom_point()`).
## Warning: Removed 47 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 47 rows containing missing values (`geom_point()`).
## Warning: Removed 49 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 49 rows containing missing values (`geom_point()`).
## Warning: Removed 59 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 59 rows containing missing values (`geom_point()`).
## Warning: Removed 49 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 49 rows containing missing values (`geom_point()`).
## Warning: Removed 57 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 57 rows containing missing values (`geom_point()`).
## Warning: Removed 51 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 51 rows containing missing values (`geom_point()`).
## Warning: Removed 55 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 55 rows containing missing values (`geom_point()`).
## Warning: Removed 70 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 70 rows containing missing values (`geom_point()`).
## Warning: Removed 69 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 69 rows containing missing values (`geom_point()`).
## Warning: Removed 36 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 36 rows containing missing values (`geom_point()`).
## Warning: Removed 57 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 57 rows containing missing values (`geom_point()`).
## Warning: Removed 67 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 67 rows containing missing values (`geom_point()`).
## Warning: Removed 46 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 46 rows containing missing values (`geom_point()`).
## Warning: Removed 48 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 48 rows containing missing values (`geom_point()`).
## Warning: Removed 63 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 63 rows containing missing values (`geom_point()`).
## Warning: Removed 63 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 63 rows containing missing values (`geom_point()`).
## Warning: Removed 47 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 47 rows containing missing values (`geom_point()`).
## Warning: Removed 51 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 51 rows containing missing values (`geom_point()`).
## Warning: Removed 72 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 72 rows containing missing values (`geom_point()`).
## Warning: Removed 52 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 52 rows containing missing values (`geom_point()`).
## Warning: Removed 41 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 41 rows containing missing values (`geom_point()`).
## Warning: Removed 58 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 58 rows containing missing values (`geom_point()`).
## Warning: Removed 52 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 52 rows containing missing values (`geom_point()`).
## Warning: Removed 54 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 54 rows containing missing values (`geom_point()`).
## Warning: Removed 59 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 59 rows containing missing values (`geom_point()`).
## Warning: Removed 58 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 58 rows containing missing values (`geom_point()`).
## Warning: Removed 48 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 48 rows containing missing values (`geom_point()`).
## Warning: Removed 24 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 24 rows containing missing values (`geom_point()`).
## Warning: Removed 65 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 65 rows containing missing values (`geom_point()`).
## Warning: Removed 51 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 51 rows containing missing values (`geom_point()`).
##By Site - GABA
SITE_IDs = unique(midlandsdataMOA$SITE_ID)
midlandsdataMOA_pest_rich_plots = list()
for(SITE_ID_ in SITE_IDs) {
midlandsdataMOA_pest_rich_plots[[SITE_ID_]] = ggplot(midlandsdataMOA %>% filter(SITE_ID == SITE_ID_), aes(x=GABA_receptor, y=distinct_families)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme_bw() + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10')
print(midlandsdataMOA_pest_rich_plots[[SITE_ID_]])
ggsave(midlandsdataMOA_pest_rich_plots[[SITE_ID_]], file=paste0("plot_", SITE_ID_," GABA Midland.png"), dpi=300)
}## Warning: Removed 52 rows containing missing values (`geom_point()`).## Saving 7 x 5 in image## Warning: Removed 52 rows containing missing values (`geom_point()`).
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#FINAL PLOTS
#ANGLIAN
ACHE_ANG<- ggplot(anglaindataMOA, aes(x=AChE, y=distinctfamilies)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') + facet_wrap(~SITE_ID)
ggsave(ACHE_ANG, file=("plot_Anglia_ACHE.png"), height = 20, width = 12, dpi=300)## Warning: Removed 1831 rows containing missing values (`geom_point()`). GABA_ANG<- ggplot(anglaindataMOA, aes(x=GABA_receptor, y=distinctfamilies)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') + facet_wrap(~SITE_ID)
ggsave(GABA_ANG, file=("plot_Anglia_GABA.png"), height = 20, width = 12, dpi=300)## Warning: Removed 1743 rows containing missing values (`geom_point()`). #MIDLANDS
ACHE_Midland<- ggplot(midlandsdataMOA, aes(x=AChE, y=distinct_families)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') + facet_wrap(~SITE_ID)
ggsave(ACHE_Midland, file=("plot_Midland_ACHE.png"), height = 20, width = 12, dpi=300)## Warning: Removed 2079 rows containing missing values (`geom_point()`). GABA_Midland<- ggplot(midlandsdataMOA, aes(x=GABA_receptor, y=distinct_families)) + geom_point() + theme(axis.text.x = element_text(angle = 90)) + ylab("Family richness") + xlab("Concentration (µg/l)") + theme(plot.title = element_text(size = 32, face = "bold", hjust=0.5), axis.title.x = element_text(size = 18, face = "bold"), axis.title.y = element_text(size = 18, face = "bold")) + scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') + facet_wrap(~SITE_ID)
ggsave(GABA_Midland, file=("plot_Midland_GABA.png"), height = 20, width = 12, dpi=300)## Warning: Removed 2098 rows containing missing values (`geom_point()`).